# config/tasks.yaml
# Task configuration reference for Cascade Containment.
# These values are the source of truth used in server/constants.py TASK_CONFIG.
# If you change a value here, update constants.py to match.

tasks:

  easy:
    num_districts: 2
    max_steps:     10
    resource_pool: 10
    data_lag_days: 0
    seed_infections: [0.06, 0.50]
    description: >
      Single outbreak. D1 starts in the danger zone, D0 is clean.
      Agents that ignore infection data and always target D0 score ~43%
      with a 60% hospital breach rate — the task requires basic observation.

  medium:
    num_districts: 4
    max_steps:     15
    resource_pool: 8
    data_lag_days: 0
    seed_infections: [0.42, 0.10, 0.38, 0.10]
    description: >
      Two simultaneous outbreaks in D0 and D2. D1 and D3 start low but
      grow into the danger zone within 4-6 steps via spillover.
      8 resources across 4 districts over 15 steps requires real triage —
      the agent cannot cover all districts at once.

  hard:
    num_districts: 6
    max_steps:     15
    resource_pool: 7
    data_lag_days: 3
    seed_infections: [0.20, 0.14, 0.23, 0.11, 0.26, 0.17]
    description: >
      Six growing outbreaks with a 3-day reporting lag. The agent sees
      infection rates from 3 days ago; true infection is already higher.
      Growth hints provide a noisy estimate of current trajectory.
      7 resources for 6 districts under structural uncertainty is the
      hardest triage scenario in the benchmark.

# Spread model parameters
spread:
  rate_min:             0.03   # minimum spread rate per district per day
  rate_max:             0.08   # maximum spread rate per district per day
  natural_recovery:     0.01   # passive case resolution per day (no intervention)
  treatment_reduction:  0.05   # allocate reduces existing infection by this
  allocate_reduction:   0.10   # allocate suppresses future spread rate this step
  restrict_reduction:   0.05   # restrict reduces spread rate while active
  spillover_rate:       0.01   # infection bleed to adjacent districts each step
  growth_hint_noise:    0.03   # noise added to spread rate in agent observation

# Threshold values
thresholds:
  infection_danger:     0.40   # above this a district is in the danger zone
  infection_safe:       0.20   # below this a district is considered contained
  hospital_breach:      0.10   # at or below this triggers episode failure

# Reward terms
rewards:
  infection_penalty:        -0.50  # per district above infection_danger, weighted by density
  hospital_breach:          -1.00  # per district at or below hospital_breach threshold
  early_containment:        +0.50  # per district below infection_safe (decays over time)
  unnecessary_restriction:  -0.20  # restricting a district already below infection_safe
  correct_prioritisation:   +0.30  # allocating to the highest-infected district

# Grader weights (must sum to 1.0)
grader:
  containment: 0.30
  hospital:    0.45
  efficiency:  0.15
  speed:       0.10

# Baseline benchmark results (update after each full evaluation run)
benchmark:
  rollouts:
    easy:   2
    medium: 3
    hard:   3
  greedy_d0:
    easy:   {score: 0.428, breach_rate: 0.60}
    medium: {score: 0.396, breach_rate: 1.00}
    hard:   {score: 0.353, breach_rate: 1.00}
  llm_grpo:
    easy:   {score: 0.885, model: llama-3.1-8b-instant}
    medium: {score: 0.780, model: llama-3.1-8b-instant}
    hard:   {score: 0.611, model: llama-3.1-8b-instant}
    average: 0.794
    runtime_seconds: 1134