task stringclasses 2
values | metadata dict | prompt stringlengths 402 1.87k | answer stringclasses 99
values | n_nodes int64 3 5 |
|---|---|---|---|---|
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 2,
"size": null... | System:
P(X_0) = {'0': 0.47, '1': 0.53}
P(X_2|X_0=0, X_1=0) = {'0': 0.3, '1': 0.7}
P(X_2|X_0=0, X_1=1) = {'0': 0.29, '1': 0.71}
P(X_2|X_0=1, X_1=0) = {'0': 0.81, '1': 0.19}
P(X_2|X_0=1, X_1=1) = {'0': 0.63, '1': 0.37}
P(X_1) = {'0': 0.47, '1': 0.53}
Observed conditions:
Observing/Knowing that the state X_2 is equa... | {0: 0.69, 1: 0.31} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 2,
"size": null... | System:
P(X_0) = {'0': 0.47, '1': 0.53}
P(X_2|X_0=0, X_1=0) = {'0': 0.3, '1': 0.7}
P(X_2|X_0=0, X_1=1) = {'0': 0.29, '1': 0.71}
P(X_2|X_0=1, X_1=0) = {'0': 0.81, '1': 0.19}
P(X_2|X_0=1, X_1=1) = {'0': 0.63, '1': 0.37}
P(X_1) = {'0': 0.47, '1': 0.53}
Observed conditions:
Doing/Imposing that the state X_2 is equal t... | {0: 0.47, 1: 0.53} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 4,
"size": null... | System:
P(X_0) = {'0': 0.65, '1': 0.35}
P(X_1|X_0=0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=1) = {'0': 0.86, '1': 0.14}
P(X_2|X_0=0) = {'0': 0.49, '1': 0.51}
P(X_2|X_0=1) = {'0': 0.86, '1': 0.14}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 1, and the state X_2 is equal to 0
Task: Compute proba... | {0: 0.79, 1: 0.21} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 4,
"size": null... | System:
P(X_0) = {'0': 0.65, '1': 0.35}
P(X_1|X_0=0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=1) = {'0': 0.86, '1': 0.14}
P(X_2|X_0=0) = {'0': 0.49, '1': 0.51}
P(X_2|X_0=1) = {'0': 0.86, '1': 0.14}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1. Observing/Knowing that the state X_2 is equal to 0
Tas... | {0: 0.51, 1: 0.49} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 7,
"size": null... | System:
P(X_0) = {'0': 0.41, '1': 0.59}
P(X_1|X_0=0) = {'0': 0.45, '1': 0.55}
P(X_1|X_0=1) = {'0': 0.8, '1': 0.2}
P(X_2|X_0=0, X_1=0) = {'0': 0.68, '1': 0.32}
P(X_2|X_0=0, X_1=1) = {'0': 0.51, '1': 0.49}
P(X_2|X_0=1, X_1=0) = {'0': 0.99, '1': 0.01}
P(X_2|X_0=1, X_1=1) = {'0': 0.22, '1': 0.78}
Observed conditions:... | {0: 0.81, 1: 0.19} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 7,
"size": null... | System:
P(X_0) = {'0': 0.41, '1': 0.59}
P(X_1|X_0=0) = {'0': 0.45, '1': 0.55}
P(X_1|X_0=1) = {'0': 0.8, '1': 0.2}
P(X_2|X_0=0, X_1=0) = {'0': 0.68, '1': 0.32}
P(X_2|X_0=0, X_1=1) = {'0': 0.51, '1': 0.49}
P(X_2|X_0=1, X_1=0) = {'0': 0.99, '1': 0.01}
P(X_2|X_0=1, X_1=1) = {'0': 0.22, '1': 0.78}
Observed conditions:... | {0: 0.66, 1: 0.34} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 15,
"size": nul... | System:
P(X_0) = {'0': 0.46, '1': 0.54}
P(X_1|X_0=0) = {'0': 0.67, '1': 0.33}
P(X_1|X_0=1) = {'0': 0.95, '1': 0.05}
P(X_2) = {'0': 0.46, '1': 0.54}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (possible values: [0, 1]).
Output: Python dict ma... | {0: 0.38, 1: 0.62} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 15,
"size": nul... | System:
P(X_0) = {'0': 0.46, '1': 0.54}
P(X_1|X_0=0) = {'0': 0.67, '1': 0.33}
P(X_1|X_0=1) = {'0': 0.95, '1': 0.05}
P(X_2) = {'0': 0.46, '1': 0.54}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (possible values: [0, 1]).
Output: Python dict mappi... | {0: 0.46, 1: 0.54} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 18,
"size": nul... | System:
P(X_0) = {'0': 0.36, '1': 0.64}
P(X_1|X_0=0) = {'0': 0.59, '1': 0.41}
P(X_1|X_0=1) = {'0': 0.9, '1': 0.1}
P(X_2|X_1=0) = {'0': 0.59, '1': 0.41}
P(X_2|X_1=1) = {'0': 0.9, '1': 0.1}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (possible... | {0: 0.3, 1: 0.7} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 18,
"size": nul... | System:
P(X_0) = {'0': 0.36, '1': 0.64}
P(X_1|X_0=0) = {'0': 0.59, '1': 0.41}
P(X_1|X_0=1) = {'0': 0.9, '1': 0.1}
P(X_2|X_1=0) = {'0': 0.59, '1': 0.41}
P(X_2|X_1=1) = {'0': 0.9, '1': 0.1}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (possible va... | {0: 0.36, 1: 0.64} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 21,
"size": nul... | System:
P(X_0) = {'0': 0.56, '1': 0.44}
P(X_1|X_0=0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=1) = {'0': 0.87, '1': 0.13}
P(X_2|X_0=0, X_1=0) = {'0': 0.55, '1': 0.45}
P(X_2|X_0=0, X_1=1) = {'0': 0.38, '1': 0.62}
P(X_2|X_0=1, X_1=0) = {'0': 0.63, '1': 0.37}
P(X_2|X_0=1, X_1=1) = {'0': 0.44, '1': 0.56}
Observed condition... | {0: 0.48, 1: 0.52} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 21,
"size": nul... | System:
P(X_0) = {'0': 0.56, '1': 0.44}
P(X_1|X_0=0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=1) = {'0': 0.87, '1': 0.13}
P(X_2|X_0=0, X_1=0) = {'0': 0.55, '1': 0.45}
P(X_2|X_0=0, X_1=1) = {'0': 0.38, '1': 0.62}
P(X_2|X_0=1, X_1=0) = {'0': 0.63, '1': 0.37}
P(X_2|X_0=1, X_1=1) = {'0': 0.44, '1': 0.56}
Observed condition... | {0: 0.61, 1: 0.39} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 22,
"size": nul... | System:
P(X_1) = {'0': 0.65, '1': 0.35}
P(X_2|X_1=0) = {'0': 0.81, '1': 0.19}
P(X_2|X_1=1) = {'0': 0.23, '1': 0.77}
P(X_0) = {'0': 0.65, '1': 0.35}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1
Task: Compute probability distribution for X_1 (possible values: [0, 1]).
Output: Python dict ma... | {0: 0.31, 1: 0.69} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 22,
"size": nul... | System:
P(X_1) = {'0': 0.65, '1': 0.35}
P(X_2|X_1=0) = {'0': 0.81, '1': 0.19}
P(X_2|X_1=1) = {'0': 0.23, '1': 0.77}
P(X_0) = {'0': 0.65, '1': 0.35}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 1
Task: Compute probability distribution for X_1 (possible values: [0, 1]).
Output: Python dict mappi... | {0: 0.65, 1: 0.35} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 28,
"size": nul... | System:
P(X_0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=0) = {'0': 0.53, '1': 0.47}
P(X_1|X_0=1) = {'0': 0.96, '1': 0.04}
P(X_2|X_0=0) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=1) = {'0': 0.96, '1': 0.04}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (poss... | {0: 0.35, 1: 0.65} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 28,
"size": nul... | System:
P(X_0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=0) = {'0': 0.53, '1': 0.47}
P(X_1|X_0=1) = {'0': 0.96, '1': 0.04}
P(X_2|X_0=0) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=1) = {'0': 0.96, '1': 0.04}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (possibl... | {0: 0.49, 1: 0.51} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 29,
"size": nul... | System:
P(X_0) = {'0': 0.09, '1': 0.91}
P(X_1|X_0=0) = {'0': 0.09, '1': 0.91}
P(X_1|X_0=1) = {'0': 0.66, '1': 0.34}
P(X_2|X_0=0) = {'0': 0.09, '1': 0.91}
P(X_2|X_0=1) = {'0': 0.66, '1': 0.34}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 1
Task: Compute probability distribution for X_2 (poss... | {0: 0.54, 1: 0.46} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 29,
"size": nul... | System:
P(X_0) = {'0': 0.09, '1': 0.91}
P(X_1|X_0=0) = {'0': 0.09, '1': 0.91}
P(X_1|X_0=1) = {'0': 0.66, '1': 0.34}
P(X_2|X_0=0) = {'0': 0.09, '1': 0.91}
P(X_2|X_0=1) = {'0': 0.66, '1': 0.34}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1
Task: Compute probability distribution for X_2 (possibl... | {0: 0.61, 1: 0.39} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 31,
"size": nul... | System:
P(X_0) = {'0': 0.93, '1': 0.07}
P(X_2|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1) = {'0': 0.13, '1': 0.87}
P(X_1) = {'0': 0.93, '1': 0.07}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 0, and the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (possible values:... | {0: 0.98, 1: 0.02} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 31,
"size": nul... | System:
P(X_0) = {'0': 0.93, '1': 0.07}
P(X_2|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1) = {'0': 0.13, '1': 0.87}
P(X_1) = {'0': 0.93, '1': 0.07}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 0. Observing/Knowing that the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (... | {0: 0.93, 1: 0.07} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 32,
"size": nul... | System:
P(X_0) = {'0': 0.22, '1': 0.78}
P(X_1|X_0=0) = {'0': 0.3, '1': 0.7}
P(X_1|X_0=1) = {'0': 0.64, '1': 0.36}
P(X_2|X_1=0) = {'0': 0.3, '1': 0.7}
P(X_2|X_1=1) = {'0': 0.64, '1': 0.36}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 1
Task: Compute probability distribution for X_0 (possible... | {0: 0.35, 1: 0.65} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 32,
"size": nul... | System:
P(X_0) = {'0': 0.22, '1': 0.78}
P(X_1|X_0=0) = {'0': 0.3, '1': 0.7}
P(X_1|X_0=1) = {'0': 0.64, '1': 0.36}
P(X_2|X_1=0) = {'0': 0.3, '1': 0.7}
P(X_2|X_1=1) = {'0': 0.64, '1': 0.36}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1
Task: Compute probability distribution for X_0 (possible va... | {0: 0.22, 1: 0.78} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 39,
"size": nul... | System:
P(X_0) = {'0': 0.48, '1': 0.52}
P(X_1|X_0=0) = {'0': 0.79, '1': 0.21}
P(X_1|X_0=1) = {'0': 0.64, '1': 0.36}
P(X_2|X_1=0) = {'0': 0.79, '1': 0.21}
P(X_2|X_1=1) = {'0': 0.64, '1': 0.36}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 0, and the state X_1 is equal to 0
Task: Compute proba... | {0: 0.53, 1: 0.47} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 39,
"size": nul... | System:
P(X_0) = {'0': 0.48, '1': 0.52}
P(X_1|X_0=0) = {'0': 0.79, '1': 0.21}
P(X_1|X_0=1) = {'0': 0.64, '1': 0.36}
P(X_2|X_1=0) = {'0': 0.79, '1': 0.21}
P(X_2|X_1=1) = {'0': 0.64, '1': 0.36}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 0. Observing/Knowing that the state X_2 is equal to 0
Tas... | {0: 0.48, 1: 0.52} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 50,
"size": nul... | System:
P(X_0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=0) = {'0': 0.59, '1': 0.41}
P(X_1|X_0=1) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=0, X_1=0) = {'0': 0.77, '1': 0.23}
P(X_2|X_0=0, X_1=1) = {'0': 0.56, '1': 0.44}
P(X_2|X_0=1, X_1=0) = {'0': 0.89, '1': 0.11}
P(X_2|X_0=1, X_1=1) = {'0': 0.64, '1': 0.36}
Observed condition... | {0: 0.21, 1: 0.79} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 50,
"size": nul... | System:
P(X_0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=0) = {'0': 0.59, '1': 0.41}
P(X_1|X_0=1) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=0, X_1=0) = {'0': 0.77, '1': 0.23}
P(X_2|X_0=0, X_1=1) = {'0': 0.56, '1': 0.44}
P(X_2|X_0=1, X_1=0) = {'0': 0.89, '1': 0.11}
P(X_2|X_0=1, X_1=1) = {'0': 0.64, '1': 0.36}
Observed condition... | {0: 0.46, 1: 0.54} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 52,
"size": nul... | System:
P(X_0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=0) = {'0': 0.54, '1': 0.46}
P(X_1|X_0=1) = {'0': 0.99, '1': 0.01}
P(X_2|X_0=0, X_1=0) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=0, X_1=1) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=0) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=1) = {'0': 0.29, '1': 0.71}
Observed condition... | {0: 0.69, 1: 0.31} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 52,
"size": nul... | System:
P(X_0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=0) = {'0': 0.54, '1': 0.46}
P(X_1|X_0=1) = {'0': 0.99, '1': 0.01}
P(X_2|X_0=0, X_1=0) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=0, X_1=1) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=0) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=1) = {'0': 0.29, '1': 0.71}
Observed condition... | {0: 0.76, 1: 0.24} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 66,
"size": nul... | System:
P(X_0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=0) = {'0': 0.93, '1': 0.07}
P(X_1|X_0=1) = {'0': 0.53, '1': 0.47}
P(X_2|X_1=0) = {'0': 0.93, '1': 0.07}
P(X_2|X_1=1) = {'0': 0.53, '1': 0.47}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1, and the state X_1 is equal to 1
Task: Compute proba... | {0: 0.16, 1: 0.84} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 66,
"size": nul... | System:
P(X_0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=0) = {'0': 0.93, '1': 0.07}
P(X_1|X_0=1) = {'0': 0.53, '1': 0.47}
P(X_2|X_1=0) = {'0': 0.93, '1': 0.07}
P(X_2|X_1=1) = {'0': 0.53, '1': 0.47}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1. Observing/Knowing that the state X_2 is equal to 1
Tas... | {0: 0.57, 1: 0.43} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 71,
"size": nul... | System:
P(X_0) = {'0': 0.32, '1': 0.68}
P(X_1|X_0=0) = {'0': 0.25, '1': 0.75}
P(X_1|X_0=1) = {'0': 0.45, '1': 0.55}
P(X_2|X_0=0) = {'0': 0.25, '1': 0.75}
P(X_2|X_0=1) = {'0': 0.45, '1': 0.55}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (poss... | {0: 0.41, 1: 0.59} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 71,
"size": nul... | System:
P(X_0) = {'0': 0.32, '1': 0.68}
P(X_1|X_0=0) = {'0': 0.25, '1': 0.75}
P(X_1|X_0=1) = {'0': 0.45, '1': 0.55}
P(X_2|X_0=0) = {'0': 0.25, '1': 0.75}
P(X_2|X_0=1) = {'0': 0.45, '1': 0.55}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (possibl... | {0: 0.39, 1: 0.61} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 74,
"size": nul... | System:
P(X_0) = {'0': 0.63, '1': 0.37}
P(X_1|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=1) = {'0': 0.44, '1': 0.56}
P(X_2|X_0=0, X_1=0) = {'0': 0.61, '1': 0.39}
P(X_2|X_0=0, X_1=1) = {'0': 0.5, '1': 0.5}
P(X_2|X_0=1, X_1=0) = {'0': 0.99, '1': 0.01}
P(X_2|X_0=1, X_1=1) = {'0': 0.47, '1': 0.53}
Observed conditions:... | {0: 0.73, 1: 0.27} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 74,
"size": nul... | System:
P(X_0) = {'0': 0.63, '1': 0.37}
P(X_1|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=1) = {'0': 0.44, '1': 0.56}
P(X_2|X_0=0, X_1=0) = {'0': 0.61, '1': 0.39}
P(X_2|X_0=0, X_1=1) = {'0': 0.5, '1': 0.5}
P(X_2|X_0=1, X_1=0) = {'0': 0.99, '1': 0.01}
P(X_2|X_0=1, X_1=1) = {'0': 0.47, '1': 0.53}
Observed conditions:... | {0: 0.75, 1: 0.25} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 78,
"size": nul... | System:
P(X_0) = {'0': 0.31, '1': 0.69}
P(X_1|X_0=0) = {'0': 0.45, '1': 0.55}
P(X_1|X_0=1) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=0, X_1=0) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=0, X_1=1) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=1, X_1=0) = {'0': 0.58, '1': 0.42}
P(X_2|X_0=1, X_1=1) = {'0': 0.72, '1': 0.28}
Observed condition... | {0: 0.35, 1: 0.65} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 78,
"size": nul... | System:
P(X_0) = {'0': 0.31, '1': 0.69}
P(X_1|X_0=0) = {'0': 0.45, '1': 0.55}
P(X_1|X_0=1) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=0, X_1=0) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=0, X_1=1) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=1, X_1=0) = {'0': 0.58, '1': 0.42}
P(X_2|X_0=1, X_1=1) = {'0': 0.72, '1': 0.28}
Observed condition... | {0: 0.31, 1: 0.69} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 79,
"size": nul... | System:
P(X_0) = {'0': 0.93, '1': 0.07}
P(X_2|X_0=0) = {'0': 0.5, '1': 0.5}
P(X_2|X_0=1) = {'0': 0.67, '1': 0.33}
P(X_1) = {'0': 0.93, '1': 0.07}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 0, and the state X_2 is equal to 0
Task: Compute probability distribution for X_0 (possible values: [... | {0: 0.91, 1: 0.09} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 79,
"size": nul... | System:
P(X_0) = {'0': 0.93, '1': 0.07}
P(X_2|X_0=0) = {'0': 0.5, '1': 0.5}
P(X_2|X_0=1) = {'0': 0.67, '1': 0.33}
P(X_1) = {'0': 0.93, '1': 0.07}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 0. Observing/Knowing that the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (po... | {0: 0.93, 1: 0.07} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 81,
"size": nul... | System:
P(X_0) = {'0': 0.67, '1': 0.33}
P(X_2|X_0=0, X_1=0) = {'0': 0.49, '1': 0.51}
P(X_2|X_0=0, X_1=1) = {'0': 0.3, '1': 0.7}
P(X_2|X_0=1, X_1=0) = {'0': 0.66, '1': 0.34}
P(X_2|X_0=1, X_1=1) = {'0': 0.86, '1': 0.14}
P(X_1) = {'0': 0.67, '1': 0.33}
Observed conditions:
Observing/Knowing that the state X_2 is equa... | {0: 0.6, 1: 0.4} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 81,
"size": nul... | System:
P(X_0) = {'0': 0.67, '1': 0.33}
P(X_2|X_0=0, X_1=0) = {'0': 0.49, '1': 0.51}
P(X_2|X_0=0, X_1=1) = {'0': 0.3, '1': 0.7}
P(X_2|X_0=1, X_1=0) = {'0': 0.66, '1': 0.34}
P(X_2|X_0=1, X_1=1) = {'0': 0.86, '1': 0.14}
P(X_1) = {'0': 0.67, '1': 0.33}
Observed conditions:
Doing/Imposing that the state X_2 is equal t... | {0: 0.67, 1: 0.33} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 86,
"size": nul... | System:
P(X_0) = {'0': 0.78, '1': 0.22}
P(X_2|X_0=0, X_1=0) = {'0': 0.63, '1': 0.37}
P(X_2|X_0=0, X_1=1) = {'0': 0.18, '1': 0.82}
P(X_2|X_0=1, X_1=0) = {'0': 0.39, '1': 0.61}
P(X_2|X_0=1, X_1=1) = {'0': 0.74, '1': 0.26}
P(X_1) = {'0': 0.78, '1': 0.22}
Observed conditions:
Observing/Knowing that the state X_2 is eq... | {0: 0.92, 1: 0.08} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 86,
"size": nul... | System:
P(X_0) = {'0': 0.78, '1': 0.22}
P(X_2|X_0=0, X_1=0) = {'0': 0.63, '1': 0.37}
P(X_2|X_0=0, X_1=1) = {'0': 0.18, '1': 0.82}
P(X_2|X_0=1, X_1=0) = {'0': 0.39, '1': 0.61}
P(X_2|X_0=1, X_1=1) = {'0': 0.74, '1': 0.26}
P(X_1) = {'0': 0.78, '1': 0.22}
Observed conditions:
Doing/Imposing that the state X_2 is equal... | {0: 0.78, 1: 0.22} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 87,
"size": nul... | System:
P(X_0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=0) = {'0': 0.77, '1': 0.23}
P(X_1|X_0=1) = {'0': 0.62, '1': 0.38}
P(X_2) = {'0': 0.42, '1': 0.58}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 1
Task: Compute probability distribution for X_0 (possible values: [0, 1]).
Output: Python dict ma... | {0: 0.3, 1: 0.7} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 87,
"size": nul... | System:
P(X_0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=0) = {'0': 0.77, '1': 0.23}
P(X_1|X_0=1) = {'0': 0.62, '1': 0.38}
P(X_2) = {'0': 0.42, '1': 0.58}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1
Task: Compute probability distribution for X_0 (possible values: [0, 1]).
Output: Python dict mappi... | {0: 0.42, 1: 0.58} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 88,
"size": nul... | System:
P(X_0) = {'0': 0.23, '1': 0.77}
P(X_1|X_0=0) = {'0': 0.23, '1': 0.77}
P(X_1|X_0=1) = {'0': 0.51, '1': 0.49}
P(X_2|X_0=0) = {'0': 0.23, '1': 0.77}
P(X_2|X_0=1) = {'0': 0.51, '1': 0.49}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (poss... | {0: 0.48, 1: 0.52} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 88,
"size": nul... | System:
P(X_0) = {'0': 0.23, '1': 0.77}
P(X_1|X_0=0) = {'0': 0.23, '1': 0.77}
P(X_1|X_0=1) = {'0': 0.51, '1': 0.49}
P(X_2|X_0=0) = {'0': 0.23, '1': 0.77}
P(X_2|X_0=1) = {'0': 0.51, '1': 0.49}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (possibl... | {0: 0.45, 1: 0.55} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 89,
"size": nul... | System:
P(X_0) = {'0': 0.43, '1': 0.57}
P(X_1|X_0=0) = {'0': 0.44, '1': 0.56}
P(X_1|X_0=1) = {'0': 0.98, '1': 0.02}
P(X_2|X_0=0, X_1=0) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=0, X_1=1) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=1, X_1=0) = {'0': 0.48, '1': 0.52}
P(X_2|X_0=1, X_1=1) = {'0': 0.03, '1': 0.97}
Observed condition... | {0: 0.27, 1: 0.73} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 89,
"size": nul... | System:
P(X_0) = {'0': 0.43, '1': 0.57}
P(X_1|X_0=0) = {'0': 0.44, '1': 0.56}
P(X_1|X_0=1) = {'0': 0.98, '1': 0.02}
P(X_2|X_0=0, X_1=0) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=0, X_1=1) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=1, X_1=0) = {'0': 0.48, '1': 0.52}
P(X_2|X_0=1, X_1=1) = {'0': 0.03, '1': 0.97}
Observed condition... | {0: 0.25, 1: 0.75} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 90,
"size": nul... | System:
P(X_0) = {'0': 0.35, '1': 0.65}
P(X_1|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=1) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_2|X_0=1) = {'0': 0.62, '1': 0.38}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (poss... | {0: 0.45, 1: 0.55} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 90,
"size": nul... | System:
P(X_0) = {'0': 0.35, '1': 0.65}
P(X_1|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=1) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_2|X_0=1) = {'0': 0.62, '1': 0.38}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (possibl... | {0: 0.35, 1: 0.65} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 91,
"size": nul... | System:
P(X_0) = {'0': 0.24, '1': 0.76}
P(X_1|X_0=0) = {'0': 0.26, '1': 0.74}
P(X_1|X_0=1) = {'0': 0.76, '1': 0.24}
P(X_2|X_0=0, X_1=0) = {'0': 0.25, '1': 0.75}
P(X_2|X_0=0, X_1=1) = {'0': 0.5, '1': 0.5}
P(X_2|X_0=1, X_1=0) = {'0': 0.74, '1': 0.26}
P(X_2|X_0=1, X_1=1) = {'0': 0.25, '1': 0.75}
Observed conditions:... | {0: 0.49, 1: 0.51} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 91,
"size": nul... | System:
P(X_0) = {'0': 0.24, '1': 0.76}
P(X_1|X_0=0) = {'0': 0.26, '1': 0.74}
P(X_1|X_0=1) = {'0': 0.76, '1': 0.24}
P(X_2|X_0=0, X_1=0) = {'0': 0.25, '1': 0.75}
P(X_2|X_0=0, X_1=1) = {'0': 0.5, '1': 0.5}
P(X_2|X_0=1, X_1=0) = {'0': 0.74, '1': 0.26}
P(X_2|X_0=1, X_1=1) = {'0': 0.25, '1': 0.75}
Observed conditions:... | {0: 0.24, 1: 0.76} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 96,
"size": nul... | System:
P(X_0) = {'0': 0.5, '1': 0.5}
P(X_1|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=1) = {'0': 0.6, '1': 0.4}
P(X_2|X_0=0, X_1=0) = {'0': 0.58, '1': 0.42}
P(X_2|X_0=0, X_1=1) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=1, X_1=0) = {'0': 0.86, '1': 0.14}
P(X_2|X_0=1, X_1=1) = {'0': 0.34, '1': 0.66}
Observed conditions:
O... | {0: 0.79, 1: 0.21} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 96,
"size": nul... | System:
P(X_0) = {'0': 0.5, '1': 0.5}
P(X_1|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=1) = {'0': 0.6, '1': 0.4}
P(X_2|X_0=0, X_1=0) = {'0': 0.58, '1': 0.42}
P(X_2|X_0=0, X_1=1) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=1, X_1=0) = {'0': 0.86, '1': 0.14}
P(X_2|X_0=1, X_1=1) = {'0': 0.34, '1': 0.66}
Observed conditions:
D... | {0: 0.6, 1: 0.4} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 100,
"size": nu... | System:
P(X_0) = {'0': 0.58, '1': 0.42}
P(X_1|X_0=0) = {'0': 0.74, '1': 0.26}
P(X_1|X_0=1) = {'0': 0.93, '1': 0.07}
P(X_2|X_1=0) = {'0': 0.74, '1': 0.26}
P(X_2|X_1=1) = {'0': 0.93, '1': 0.07}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1, and the state X_1 is equal to 1
Task: Compute proba... | {0: 0.84, 1: 0.16} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 100,
"size": nu... | System:
P(X_0) = {'0': 0.58, '1': 0.42}
P(X_1|X_0=0) = {'0': 0.74, '1': 0.26}
P(X_1|X_0=1) = {'0': 0.93, '1': 0.07}
P(X_2|X_1=0) = {'0': 0.74, '1': 0.26}
P(X_2|X_1=1) = {'0': 0.93, '1': 0.07}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1. Observing/Knowing that the state X_2 is equal to 1
Tas... | {0: 0.58, 1: 0.42} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 101,
"size": nu... | System:
P(X_0) = {'0': 0.72, '1': 0.28}
P(X_2|X_0=0, X_1=0) = {'0': 0.76, '1': 0.24}
P(X_2|X_0=0, X_1=1) = {'0': 0.28, '1': 0.72}
P(X_2|X_0=1, X_1=0) = {'0': 0.47, '1': 0.53}
P(X_2|X_0=1, X_1=1) = {'0': 0.62, '1': 0.38}
P(X_1) = {'0': 0.72, '1': 0.28}
Observed conditions:
Observing/Knowing that the state X_2 is eq... | {0: 0.57, 1: 0.43} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 101,
"size": nu... | System:
P(X_0) = {'0': 0.72, '1': 0.28}
P(X_2|X_0=0, X_1=0) = {'0': 0.76, '1': 0.24}
P(X_2|X_0=0, X_1=1) = {'0': 0.28, '1': 0.72}
P(X_2|X_0=1, X_1=0) = {'0': 0.47, '1': 0.53}
P(X_2|X_0=1, X_1=1) = {'0': 0.62, '1': 0.38}
P(X_1) = {'0': 0.72, '1': 0.28}
Observed conditions:
Doing/Imposing that the state X_2 is equal... | {0: 0.72, 1: 0.28} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 104,
"size": nu... | System:
P(X_0) = {'0': 0.55, '1': 0.45}
P(X_1|X_0=0) = {'0': 0.8, '1': 0.2}
P(X_1|X_0=1) = {'0': 0.85, '1': 0.15}
P(X_2|X_1=0) = {'0': 0.8, '1': 0.2}
P(X_2|X_1=1) = {'0': 0.85, '1': 0.15}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 1
Task: Compute probability distribution for X_0 (possible... | {0: 0.62, 1: 0.38} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 104,
"size": nu... | System:
P(X_0) = {'0': 0.55, '1': 0.45}
P(X_1|X_0=0) = {'0': 0.8, '1': 0.2}
P(X_1|X_0=1) = {'0': 0.85, '1': 0.15}
P(X_2|X_1=0) = {'0': 0.8, '1': 0.2}
P(X_2|X_1=1) = {'0': 0.85, '1': 0.15}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1
Task: Compute probability distribution for X_0 (possible va... | {0: 0.55, 1: 0.45} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 109,
"size": nu... | System:
P(X_0) = {'0': 0.39, '1': 0.61}
P(X_1|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=1) = {'0': 0.72, '1': 0.28}
P(X_2|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_2|X_0=1) = {'0': 0.72, '1': 0.28}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1
Task: Compute probability distribution for X_1 (poss... | {0: 0.55, 1: 0.45} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 109,
"size": nu... | System:
P(X_0) = {'0': 0.39, '1': 0.61}
P(X_1|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=1) = {'0': 0.72, '1': 0.28}
P(X_2|X_0=0) = {'0': 0.42, '1': 0.58}
P(X_2|X_0=1) = {'0': 0.72, '1': 0.28}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 1
Task: Compute probability distribution for X_1 (possibl... | {0: 0.6, 1: 0.4} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 110,
"size": nu... | System:
P(X_0) = {'0': 0.64, '1': 0.36}
P(X_1|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=1) = {'0': 0.51, '1': 0.49}
P(X_2|X_0=0, X_1=0) = {'0': 0.8, '1': 0.2}
P(X_2|X_0=0, X_1=1) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=0) = {'0': 0.91, '1': 0.09}
P(X_2|X_0=1, X_1=1) = {'0': 0.42, '1': 0.58}
Observed conditions:... | {0: 0.25, 1: 0.75} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 110,
"size": nu... | System:
P(X_0) = {'0': 0.64, '1': 0.36}
P(X_1|X_0=0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=1) = {'0': 0.51, '1': 0.49}
P(X_2|X_0=0, X_1=0) = {'0': 0.8, '1': 0.2}
P(X_2|X_0=0, X_1=1) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=0) = {'0': 0.91, '1': 0.09}
P(X_2|X_0=1, X_1=1) = {'0': 0.42, '1': 0.58}
Observed conditions:... | {0: 0.55, 1: 0.45} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 117,
"size": nu... | System:
P(X_0) = {'0': 0.85, '1': 0.15}
P(X_2|X_0=0) = {'0': 0.59, '1': 0.41}
P(X_2|X_0=1) = {'0': 0.3, '1': 0.7}
P(X_1) = {'0': 0.85, '1': 0.15}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 0
Task: Compute probability distribution for X_0 (possible values: [0, 1]).
Output: Python dict mapp... | {0: 0.92, 1: 0.08} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 117,
"size": nu... | System:
P(X_0) = {'0': 0.85, '1': 0.15}
P(X_2|X_0=0) = {'0': 0.59, '1': 0.41}
P(X_2|X_0=1) = {'0': 0.3, '1': 0.7}
P(X_1) = {'0': 0.85, '1': 0.15}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 0
Task: Compute probability distribution for X_0 (possible values: [0, 1]).
Output: Python dict mapping... | {0: 0.85, 1: 0.15} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 119,
"size": nu... | System:
P(X_0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=0) = {'0': 0.54, '1': 0.46}
P(X_1|X_0=1) = {'0': 0.84, '1': 0.16}
P(X_2|X_0=0) = {'0': 0.54, '1': 0.46}
P(X_2|X_0=1) = {'0': 0.84, '1': 0.16}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (poss... | {0: 0.7, 1: 0.3} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 119,
"size": nu... | System:
P(X_0) = {'0': 0.57, '1': 0.43}
P(X_1|X_0=0) = {'0': 0.54, '1': 0.46}
P(X_1|X_0=1) = {'0': 0.84, '1': 0.16}
P(X_2|X_0=0) = {'0': 0.54, '1': 0.46}
P(X_2|X_0=1) = {'0': 0.84, '1': 0.16}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (possibl... | {0: 0.67, 1: 0.33} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 123,
"size": nu... | System:
P(X_1) = {'0': 0.93, '1': 0.07}
P(X_2|X_1=0) = {'0': 0.76, '1': 0.24}
P(X_2|X_1=1) = {'0': 0.23, '1': 0.77}
P(X_0) = {'0': 0.93, '1': 0.07}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1, and the state X_0 is equal to 0
Task: Compute probability distribution for X_1 (possible values:... | {0: 0.81, 1: 0.19} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 123,
"size": nu... | System:
P(X_1) = {'0': 0.93, '1': 0.07}
P(X_2|X_1=0) = {'0': 0.76, '1': 0.24}
P(X_2|X_1=1) = {'0': 0.23, '1': 0.77}
P(X_0) = {'0': 0.93, '1': 0.07}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 1. Observing/Knowing that the state X_0 is equal to 0
Task: Compute probability distribution for X_1 (... | {0: 0.93, 1: 0.07} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 127,
"size": nu... | System:
P(X_1) = {'0': 0.23, '1': 0.77}
P(X_2|X_1=0) = {'0': 0.17, '1': 0.83}
P(X_2|X_1=1) = {'0': 0.19, '1': 0.81}
P(X_0) = {'0': 0.23, '1': 0.77}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (possible values: [0, 1]).
Output: Python dict ma... | {0: 0.21, 1: 0.79} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 127,
"size": nu... | System:
P(X_1) = {'0': 0.23, '1': 0.77}
P(X_2|X_1=0) = {'0': 0.17, '1': 0.83}
P(X_2|X_1=1) = {'0': 0.19, '1': 0.81}
P(X_0) = {'0': 0.23, '1': 0.77}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 0
Task: Compute probability distribution for X_1 (possible values: [0, 1]).
Output: Python dict mappi... | {0: 0.23, 1: 0.77} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 131,
"size": nu... | System:
P(X_0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=0) = {'0': 0.55, '1': 0.45}
P(X_1|X_0=1) = {'0': 0.8, '1': 0.2}
P(X_2|X_0=0, X_1=0) = {'0': 0.89, '1': 0.11}
P(X_2|X_0=0, X_1=1) = {'0': 0.38, '1': 0.62}
P(X_2|X_0=1, X_1=0) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=1) = {'0': 0.21, '1': 0.79}
Observed conditions:... | {0: 0.88, 1: 0.12} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 131,
"size": nu... | System:
P(X_0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=0) = {'0': 0.55, '1': 0.45}
P(X_1|X_0=1) = {'0': 0.8, '1': 0.2}
P(X_2|X_0=0, X_1=0) = {'0': 0.89, '1': 0.11}
P(X_2|X_0=0, X_1=1) = {'0': 0.38, '1': 0.62}
P(X_2|X_0=1, X_1=0) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=1) = {'0': 0.21, '1': 0.79}
Observed conditions:... | {0: 0.8, 1: 0.2} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 132,
"size": nu... | System:
P(X_0) = {'0': 0.15, '1': 0.85}
P(X_1|X_0=0) = {'0': 0.16, '1': 0.84}
P(X_1|X_0=1) = {'0': 0.48, '1': 0.52}
P(X_2|X_0=0, X_1=0) = {'0': 0.15, '1': 0.85}
P(X_2|X_0=0, X_1=1) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=0) = {'0': 0.58, '1': 0.42}
P(X_2|X_0=1, X_1=1) = {'0': 0.48, '1': 0.52}
Observed condition... | {0: 0.46, 1: 0.54} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 132,
"size": nu... | System:
P(X_0) = {'0': 0.15, '1': 0.85}
P(X_1|X_0=0) = {'0': 0.16, '1': 0.84}
P(X_1|X_0=1) = {'0': 0.48, '1': 0.52}
P(X_2|X_0=0, X_1=0) = {'0': 0.15, '1': 0.85}
P(X_2|X_0=0, X_1=1) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=0) = {'0': 0.58, '1': 0.42}
P(X_2|X_0=1, X_1=1) = {'0': 0.48, '1': 0.52}
Observed condition... | {0: 0.43, 1: 0.57} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 138,
"size": nu... | System:
P(X_0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=0) = {'0': 0.51, '1': 0.49}
P(X_1|X_0=1) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=0, X_1=0) = {'0': 0.4, '1': 0.6}
P(X_2|X_0=0, X_1=1) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=0) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=1, X_1=1) = {'0': 0.85, '1': 0.15}
Observed conditions:... | {0: 0.31, 1: 0.69} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 138,
"size": nu... | System:
P(X_0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=0) = {'0': 0.51, '1': 0.49}
P(X_1|X_0=1) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=0, X_1=0) = {'0': 0.4, '1': 0.6}
P(X_2|X_0=0, X_1=1) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=0) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=1, X_1=1) = {'0': 0.85, '1': 0.15}
Observed conditions:... | {0: 0.4, 1: 0.6} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 139,
"size": nu... | System:
P(X_0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=0) = {'0': 0.75, '1': 0.25}
P(X_1|X_0=1) = {'0': 0.89, '1': 0.11}
P(X_2) = {'0': 0.42, '1': 0.58}
Observed conditions:
Observing/Knowing that the state X_1 is equal to 1, and the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (possible values:... | {0: 0.62, 1: 0.38} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 139,
"size": nu... | System:
P(X_0) = {'0': 0.42, '1': 0.58}
P(X_1|X_0=0) = {'0': 0.75, '1': 0.25}
P(X_1|X_0=1) = {'0': 0.89, '1': 0.11}
P(X_2) = {'0': 0.42, '1': 0.58}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 1. Observing/Knowing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (... | {0: 0.42, 1: 0.58} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 140,
"size": nu... | System:
P(X_0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=1) = {'0': 0.74, '1': 0.26}
P(X_2|X_0=0, X_1=0) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=0, X_1=1) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=1, X_1=0) = {'0': 0.6, '1': 0.4}
P(X_2|X_0=1, X_1=1) = {'0': 0.5, '1': 0.5}
Observed conditions:
O... | {0: 0.5, 1: 0.5} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 140,
"size": nu... | System:
P(X_0) = {'0': 0.52, '1': 0.48}
P(X_1|X_0=0) = {'0': 0.49, '1': 0.51}
P(X_1|X_0=1) = {'0': 0.74, '1': 0.26}
P(X_2|X_0=0, X_1=0) = {'0': 0.52, '1': 0.48}
P(X_2|X_0=0, X_1=1) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=1, X_1=0) = {'0': 0.6, '1': 0.4}
P(X_2|X_0=1, X_1=1) = {'0': 0.5, '1': 0.5}
Observed conditions:
D... | {0: 0.52, 1: 0.48} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 142,
"size": nu... | System:
P(X_0) = {'0': 0.17, '1': 0.83}
P(X_2|X_0=0, X_1=0) = {'0': 0.03, '1': 0.97}
P(X_2|X_0=0, X_1=1) = {'0': 0.11, '1': 0.89}
P(X_2|X_0=1, X_1=0) = {'0': 0.74, '1': 0.26}
P(X_2|X_0=1, X_1=1) = {'0': 0.79, '1': 0.21}
P(X_1) = {'0': 0.17, '1': 0.83}
Observed conditions:
Observing/Knowing that the state X_0 is eq... | {0: 0.2, 1: 0.8} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 142,
"size": nu... | System:
P(X_0) = {'0': 0.17, '1': 0.83}
P(X_2|X_0=0, X_1=0) = {'0': 0.03, '1': 0.97}
P(X_2|X_0=0, X_1=1) = {'0': 0.11, '1': 0.89}
P(X_2|X_0=1, X_1=0) = {'0': 0.74, '1': 0.26}
P(X_2|X_0=1, X_1=1) = {'0': 0.79, '1': 0.21}
P(X_1) = {'0': 0.17, '1': 0.83}
Observed conditions:
Doing/Imposing that the state X_2 is equal... | {0: 0.17, 1: 0.83} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 143,
"size": nu... | System:
P(X_0) = {'0': 0.3, '1': 0.7}
P(X_1|X_0=0) = {'0': 0.45, '1': 0.55}
P(X_1|X_0=1) = {'0': 0.6, '1': 0.4}
P(X_2|X_0=0, X_1=0) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=0, X_1=1) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=1, X_1=0) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=1) = {'0': 0.85, '1': 0.15}
Observed conditions:
O... | {0: 0.24, 1: 0.76} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 143,
"size": nu... | System:
P(X_0) = {'0': 0.3, '1': 0.7}
P(X_1|X_0=0) = {'0': 0.45, '1': 0.55}
P(X_1|X_0=1) = {'0': 0.6, '1': 0.4}
P(X_2|X_0=0, X_1=0) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=0, X_1=1) = {'0': 0.53, '1': 0.47}
P(X_2|X_0=1, X_1=0) = {'0': 0.57, '1': 0.43}
P(X_2|X_0=1, X_1=1) = {'0': 0.85, '1': 0.15}
Observed conditions:
D... | {0: 0.3, 1: 0.7} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 148,
"size": nu... | System:
P(X_0) = {'0': 0.54, '1': 0.46}
P(X_1|X_0=0) = {'0': 0.46, '1': 0.54}
P(X_1|X_0=1) = {'0': 0.45, '1': 0.55}
P(X_2|X_0=0, X_1=0) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=0, X_1=1) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=0) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=1, X_1=1) = {'0': 0.75, '1': 0.25}
Observed condition... | {0: 0.45, 1: 0.55} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 148,
"size": nu... | System:
P(X_0) = {'0': 0.54, '1': 0.46}
P(X_1|X_0=0) = {'0': 0.46, '1': 0.54}
P(X_1|X_0=1) = {'0': 0.45, '1': 0.55}
P(X_2|X_0=0, X_1=0) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=0, X_1=1) = {'0': 0.37, '1': 0.63}
P(X_2|X_0=1, X_1=0) = {'0': 0.46, '1': 0.54}
P(X_2|X_0=1, X_1=1) = {'0': 0.75, '1': 0.25}
Observed condition... | {0: 0.46, 1: 0.54} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 154,
"size": nu... | System:
P(X_0) = {'0': 0.47, '1': 0.53}
P(X_1|X_0=0) = {'0': 0.74, '1': 0.26}
P(X_1|X_0=1) = {'0': 0.77, '1': 0.23}
P(X_2) = {'0': 0.47, '1': 0.53}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1, and the state X_1 is equal to 0
Task: Compute probability distribution for X_0 (possible values:... | {0: 0.46, 1: 0.54} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 154,
"size": nu... | System:
P(X_0) = {'0': 0.47, '1': 0.53}
P(X_1|X_0=0) = {'0': 0.74, '1': 0.26}
P(X_1|X_0=1) = {'0': 0.77, '1': 0.23}
P(X_2) = {'0': 0.47, '1': 0.53}
Observed conditions:
Doing/Imposing that the state X_1 is equal to 0. Observing/Knowing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (... | {0: 0.47, 1: 0.53} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 162,
"size": nu... | System:
P(X_0) = {'0': 0.24, '1': 0.76}
P(X_2|X_0=0, X_1=0) = {'0': 0.94, '1': 0.06}
P(X_2|X_0=0, X_1=1) = {'0': 0.28, '1': 0.72}
P(X_2|X_0=1, X_1=0) = {'0': 0.73, '1': 0.27}
P(X_2|X_0=1, X_1=1) = {'0': 0.79, '1': 0.21}
P(X_1) = {'0': 0.24, '1': 0.76}
Observed conditions:
Observing/Knowing that the state X_2 is eq... | {0: 0.44, 1: 0.56} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 162,
"size": nu... | System:
P(X_0) = {'0': 0.24, '1': 0.76}
P(X_2|X_0=0, X_1=0) = {'0': 0.94, '1': 0.06}
P(X_2|X_0=0, X_1=1) = {'0': 0.28, '1': 0.72}
P(X_2|X_0=1, X_1=0) = {'0': 0.73, '1': 0.27}
P(X_2|X_0=1, X_1=1) = {'0': 0.79, '1': 0.21}
P(X_1) = {'0': 0.24, '1': 0.76}
Observed conditions:
Doing/Imposing that the state X_2 is equal... | {0: 0.24, 1: 0.76} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 163,
"size": nu... | System:
P(X_0) = {'0': 0.97, '1': 0.03}
P(X_2|X_0=0, X_1=0) = {'0': 0.76, '1': 0.24}
P(X_2|X_0=0, X_1=1) = {'0': 0.05, '1': 0.95}
P(X_2|X_0=1, X_1=0) = {'0': 0.61, '1': 0.39}
P(X_2|X_0=1, X_1=1) = {'0': 0.91, '1': 0.09}
P(X_1) = {'0': 0.97, '1': 0.03}
Observed conditions:
Observing/Knowing that the state X_0 is eq... | {0: 0.96, 1: 0.04} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 163,
"size": nu... | System:
P(X_0) = {'0': 0.97, '1': 0.03}
P(X_2|X_0=0, X_1=0) = {'0': 0.76, '1': 0.24}
P(X_2|X_0=0, X_1=1) = {'0': 0.05, '1': 0.95}
P(X_2|X_0=1, X_1=0) = {'0': 0.61, '1': 0.39}
P(X_2|X_0=1, X_1=1) = {'0': 0.91, '1': 0.09}
P(X_1) = {'0': 0.97, '1': 0.03}
Observed conditions:
Doing/Imposing that the state X_2 is equal... | {0: 0.97, 1: 0.03} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 166,
"size": nu... | System:
P(X_0) = {'0': 0.81, '1': 0.19}
P(X_2|X_0=0, X_1=0) = {'0': 0.43, '1': 0.57}
P(X_2|X_0=0, X_1=1) = {'0': 0.2, '1': 0.8}
P(X_2|X_0=1, X_1=0) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=1, X_1=1) = {'0': 0.61, '1': 0.39}
P(X_1) = {'0': 0.81, '1': 0.19}
Observed conditions:
Observing/Knowing that the state X_1 is equa... | {0: 0.58, 1: 0.42} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 166,
"size": nu... | System:
P(X_0) = {'0': 0.81, '1': 0.19}
P(X_2|X_0=0, X_1=0) = {'0': 0.43, '1': 0.57}
P(X_2|X_0=0, X_1=1) = {'0': 0.2, '1': 0.8}
P(X_2|X_0=1, X_1=0) = {'0': 0.62, '1': 0.38}
P(X_2|X_0=1, X_1=1) = {'0': 0.61, '1': 0.39}
P(X_1) = {'0': 0.81, '1': 0.19}
Observed conditions:
Doing/Imposing that the state X_2 is equal t... | {0: 0.81, 1: 0.19} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 167,
"size": nu... | System:
P(X_0) = {'0': 0.15, '1': 0.85}
P(X_1|X_0=0) = {'0': 0.17, '1': 0.83}
P(X_1|X_0=1) = {'0': 0.81, '1': 0.19}
P(X_2|X_0=0) = {'0': 0.17, '1': 0.83}
P(X_2|X_0=1) = {'0': 0.81, '1': 0.19}
Observed conditions:
Observing/Knowing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (poss... | {0: 0.44, 1: 0.56} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 167,
"size": nu... | System:
P(X_0) = {'0': 0.15, '1': 0.85}
P(X_1|X_0=0) = {'0': 0.17, '1': 0.83}
P(X_1|X_0=1) = {'0': 0.81, '1': 0.19}
P(X_2|X_0=0) = {'0': 0.17, '1': 0.83}
P(X_2|X_0=1) = {'0': 0.81, '1': 0.19}
Observed conditions:
Doing/Imposing that the state X_2 is equal to 1
Task: Compute probability distribution for X_0 (possibl... | {0: 0.15, 1: 0.85} | 3 |
bayesian_association | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 174,
"size": nu... | System:
P(X_0) = {'0': 0.53, '1': 0.47}
P(X_1|X_0=0) = {'0': 0.5, '1': 0.5}
P(X_1|X_0=1) = {'0': 0.67, '1': 0.33}
P(X_2|X_0=0, X_1=0) = {'0': 0.89, '1': 0.11}
P(X_2|X_0=0, X_1=1) = {'0': 0.61, '1': 0.39}
P(X_2|X_0=1, X_1=0) = {'0': 0.49, '1': 0.51}
P(X_2|X_0=1, X_1=1) = {'0': 0.32, '1': 0.68}
Observed conditions:... | {0: 0.77, 1: 0.23} | 3 |
bayesian_intervention | {
"_config": {
"c": 1,
"concise_cot": false,
"cot_scientific_notation": false,
"cpt_relative_threshold": 0,
"edge_prob": 0.5,
"graph_generation_mode": "erdos",
"is_verbose": false,
"level": 0,
"max_domain_size": 2,
"n_nodes": 3,
"n_round": 2,
"seed": 174,
"size": nu... | System:
P(X_0) = {'0': 0.53, '1': 0.47}
P(X_1|X_0=0) = {'0': 0.5, '1': 0.5}
P(X_1|X_0=1) = {'0': 0.67, '1': 0.33}
P(X_2|X_0=0, X_1=0) = {'0': 0.89, '1': 0.11}
P(X_2|X_0=0, X_1=1) = {'0': 0.61, '1': 0.39}
P(X_2|X_0=1, X_1=0) = {'0': 0.49, '1': 0.51}
P(X_2|X_0=1, X_1=1) = {'0': 0.32, '1': 0.68}
Observed conditions:... | {0: 0.68, 1: 0.32} | 3 |
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