feat: implement signal conflict modeling, distance-based noise scaling, and per-agent heterogeneity#42
Merged
stedrew merged 13 commits intodenoslab:mainfrom Mar 16, 2026
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Changes to be committed: modified: agentevac/simulation/main.py modified: agentevac/simulation/spawn_events.py modified: agentevac/utils/replay.py modified: sumo/Repaired.netecfg modified: sumo/Repaired.sumocfg
Module updated: agentevac/utils/replay.py
- Fixed RouteReplay._load_schedule(...) so it only reads step and veh_id for replayable events:
- route_change
- departure_release
- Non-replayable events like agent_cognition and metrics_snapshot are now ignored without touching veh_id.
Cause
- The loader was accessing rec["veh_id"] before checking the event type.
- metrics_snapshot records do not have veh_id, so replay loading crashed with KeyError.
Verification
1. python3 -m py_compile agentevac/utils/replay.py passed.
2. Reproduced the failing case with a small local script:
- one route_change
- one agent_cognition
- one metrics_snapshot
- replay load now succeeds and only indexes the route-change step.
…s and agent communication
…t_round_timeline.py
…gs for documentation
…g, and per-agent heterogeneity - Add compute_signal_conflict() using Jensen-Shannon divergence in belief_model.py - Restructure all three LLM prompts (pre-departure, destination, route) to expose raw env vs. social disagreement via your_observation/neighbor_assessment/ information_conflict/combined_belief fields - Add conflict_assessment field to all Pydantic response models - Add conflict recording to metrics (record_conflict_sample, compute_average_signal_conflict) - Implement distance-based noise scaling (proposal Eq. 1): effective sigma scales with fire margin / reference distance via DIST_REF_M config - Add per-agent parameter heterogeneity via sample_profile_params() with truncated normal distributions; configurable via *_SPREAD env vars (default 0 = legacy) - Fix stale subjective_information reference in scenarios.py - Add experiment stage scripts (stages 0-5) for RQ1/RQ2/RQ3 sweeps - Add comprehensive tests for all new features (291 tests passing) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
stedrew
approved these changes
Mar 16, 2026
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Summary
compute_signal_conflict()in belief model andrecord_conflict_sample()/compute_average_signal_conflict()in metricsbase_margin / D_ref, so closer fires produce less perceptual noise (inject_signal_noiseandsample_environment_signalupdated withdistance_ref_mparameter)sample_profile_params()using truncated normal distributions with hash-based deterministic RNG per agent, controlled via*_SPREADenv vars (all default 0.0 for backward compatibility)subjective_information/belief_statewithyour_observation/neighbor_assessment/information_conflict/combined_belief; fixed stale field reference inscenarios.pyTest plan
python -m pytest tests/)DIST_REF_M=500to verify distance-scaled noiseTHETA_TRUST_SPREAD=0.15 THETA_R_SPREAD=0.1to verify agent heterogeneityaverage_signal_conflictappears in metrics JSON output🤖 Generated with Claude Code