dedeucebench_hud_dev / dev_basic.json
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[
{
"id": "seed_2",
"prompt": "OBSERVATION:\n{\"alphabet\": [\"A\", \"B\", \"C\"], \"outputs\": [\"x\", \"y\", \"z\"], \"budget\": 40, \"goal\": \"basic\", \"n_states\": 3, \"target_len\": 8, \"trap\": false}\n\nEpisode notes:\n- alphabet: allowed input symbols ('A','B','C').\n- outputs: each act(symbol) produces exactly one output in {'x','y','z'}.\n- budget: total act() calls available this episode.\n- n_states: total number of states (indices 0..n-1). In explanations we refer to them as s0, s1, ..., s{n-1}. Start is s0 (index 0).\n- trap: whether trap transitions may exist; if trap_hit becomes true, success is impossible.\n\nThis is a single-trajectory, stateful, non-resetting episode: each act(symbol) advances the live machine and produces an output. Both output and next state depend on (current_state, symbol). There is no undo or rewind machine is always live. submit_table(...) does not reset state.\n\nTask: Use act() to gather enough evidence (observing the outputs), then call submit_table(table_json) with a complete table for all states s0..s{n-1} (indices 0..n-1 in JSON) and symbols A,B,C.\nIf your table is incorrect, submit_table may return a counterexample (a short input sequence from the start state with the true outputs); you may use it to adjust your hypothesis. This consumes 1 query and the episode continues.\nUse only act() and submit_table(...). Always terminate by calling submit_table(...).\n\nTool call schemas (short):\n- act(symbol: 'A'|'B'|'C') -> returns JSON {output:'x'|'y'|'z', budget_left:int, t:int, trap_hit:bool, queries_used:int}.\n- submit_table(table_json: string-of-JSON). The table_json MUST be an object with keys 'n', 'start', 'trans',\n and each symbol entry is an array [next_state:int, output:'x'|'y'|'z'] (do NOT use objects like {output:..., next_state:...}).\n Minimal example: {\"n\":2, \"start\":0, \"trans\":{\"0\":{\"A\":[1,\"x\"],\"B\":[1,\"z\"],\"C\":[1,\"z\"]},\"1\":{\"A\":[0,\"z\"],\"B\":[1,\"z\"],\"C\":[1,\"z\"]}}}.\n",
"mcp_config": {
"hud": {
"url": "https://mcp.hud.so/v3/mcp",
"headers": {
"Authorization": "Bearer ${HUD_API_KEY}",
"Run-Id": "${RUN_ID}",
"Mcp-Image": "docker.io/vedanshsharma123/dedeucebench_hud@sha256:4cd3bc40218f472d7ad945bd7a4d4aa38e3e0a77a775e92b5ac225d10042c3ee"
}
}
},
"setup_tool": {
"name": "setup",
"arguments": {
"seed": 2,
"mode": "basic",
"budget": 40,
"n_states": 3,
"target_len": 8,
"feedback": true,
"trap": false,
"variety": false,
"max_steps": 64
}
},
"evaluate_tool": {
"name": "evaluate",
"arguments": {}
},
"agent_config": {
"system_prompt": "You are an autonomous tool-using agent interacting with a hidden Mealy machine (finite-state transducer).\nObjective: exactly identify the machine and submit the full transition table via submit_table(table_json).\nReturn ONLY function tool calls; never output natural language. All responses must be valid JSON if any content is emitted.\n\nBenchmark focus: identification-first. Success is achieved only by exact transition-table submission via submit_table(table_json).\n\nEpisode semantics:\n- Stateful episode: the hidden machine's state persists across all tool calls; there are no resets between calls.\n- act(symbol) produces exactly one output (a symbol in {'x','y','z'}) and advances the hidden state; both output and next state are deterministic functions of (current_state, symbol).\n- submit_table(table_json) does not change or reset state; wrong submissions consume 1 query and the episode continues; correct submission ends the episode.\n- Start state is 0; the hidden state updates only when you call act(symbol).\n- Each act() consumes 1 query from the budget (invalid symbols still consume 1 and return an error).\n- submit_table(table_json): if your table is incorrect, it consumes 1 query and does NOT end the episode (when feedback is enabled, a short counterexample is returned). If correct, it ends the episode and does not consume budget. When budget reaches 0, the episode ends with ok=false.\n\nTools (use only act() and submit_table()):\n- act(symbol: 'A'|'B'|'C') -> JSON {output, budget_left, t, trap_hit, queries_used}. Each call consumes 1 query, produces an output, and advances the hidden state.\n- submit_table(...) -> JSON {ok, budget_left, queries_used, trap_hit, counterexample?}. If ok=false, consumes 1 query and does NOT end the episode (counterexample present only when feedback is enabled). If ok=true, ends the episode.\n\nTool return fields (definitions):\n- output: one of {'x','y','z'} produced by the latest act() call.\n- budget_left: remaining number of act() queries.\n- t: 1-based step index since the episode started (increments on each act()).\n- trap_hit: boolean; once true it remains true for the rest of the episode.\n- queries_used: total count of act() calls so far.\n\nCounterexample semantics (when feedback is enabled):\n- If submit_table is incorrect, the environment may return a short distinguishing test starting from the start state (state 0): a sequence of inputs with the corresponding true outputs.\n- This counterexample is diagnostic only. It does NOT change the live episode state, and it is NOT tied to your current state trajectory.\n- You may use it to refine your hypothesis; then continue probing with act() and resubmit.\n\nSubmit-table JSON schema (table_json string must parse to this shape, strictly follow this):\nImportant: Each entry is [next_state:int, output:'x'|'y'|'z'] \u2014 do NOT swap to [output, next_state].\n\n{\n \"n\": <int total_states>,\n \"start\": 0,\n \"trans\": {\n \"0\": { \"A\": [<ns:int>, <output:\"x\"|\"y\"|\"z\">], \"B\": [<ns>, <output>], \"C\": [<ns>, <output>] },\n \"1\": { \"A\": [<ns>, <output>], \"B\": [<ns>, <output>], \"C\": [<ns>, <output>] },\n ... up to \"n-1\"\n }\n}\n\nSkeleton example of table_json (Strictly follow this) (for n=2 \u2014 adjust values):\n{\"n\":2,\"start\":0,\"trans\":{\"0\":{\"A\":[1,\"y\"],\"B\":[0,\"x\"],\"C\":[0,\"x\"]},\"1\":{\"A\":[0,\"x\"],\"B\":[1,\"y\"],\"C\":[1,\"z\"]}}}\n\nFormatting & compliance:\n- Respond only with function tool calls as per the provided tool schemas.\n- The submit_table argument must be a single JSON string (not an object) matching the schema mentioned. Note that it include n, start and trans parts.\n- Do NOT echo the observation or tool descriptions.\n- Ensure \"trans\" covers every state index 0..n-1 and each of A,B,C exactly once.\n- Always terminate by calling submit_table(...).",
"temperature": 0,
"top_p": 1
},
"allowed_tools": [
"act",
"submit_table"
],
"max_steps": 64
}
]