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feat: Iteration_2 — trajectory reward shaping, episode jitter, flag identification
- grader.py: trajectory reward split (terminal=0.60, inv=0.20, flag_id=0.20), score clamped [0,1] - environment.py: per-episode RNG jitter (amount +/-20%, risk_score +/-0.03, velocity +/-3), episode_seed exposed - tasks.py: key_flags + network_graph on all 20 tasks (18/20 non-empty key_flags, 6 with network_graph) - models.py: episode_seed in PayOpsState, network_graph in PayOpsObservation - openenv.yaml: updated reward section with v2 split and min/max score bounds - server/app.py: /health exposes episode_seed, episode_id, task progress - README.md: documented v2 trajectory reward design and per-episode jitter - Fixes broken baseline_agent.py dict key names (terminal_action, weighted_reward) Checklist: 124/124 passed. Baseline score: 0.7552 (16/20 correct).9c003f0
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Initial Commit
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