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When Outcome Looks Right But Discipline Fails: Trace-Based Evaluation Under Hidden Competitor State

Occurred
May 18, 2026
Published
May 18, 2026
Source
arXiv

Summary

Outcome-only evaluation can certify economically unsafe agents: a policy can hit a business KPI while violating deployable behavioral discipline. In hotel pricing with hidden competitor state, a learner can achieve plausible revenue per available room while failing to preserve the rate discipline of a rule-based revenue-management competitor. We introduce discipline stability, a trace-based evaluation paradigm: define the benchmark behavior, restrict observations to the deployment regime, induce trace diagnostics from failure, separate mechanisms with ablations, and test transfer and deployment. Across a two-hotel benchmark and a compact hidden-budget bidding task, reward-only PPO variants miss trace alignment; revealing hidden state reduces label uncertainty; deterministic copy collapses uncertainty; and trace-prior or corrected history policies better preserve price or bid distributions. Pure behavior cloning is nearly enough for symmetric imitation, while Trace-Prior RL adds bounded adaptation under capacity asymmetry. The contribution is an evaluation and benchmark paradigm, not a new optimizer or a universal claim about MARL

Classification

Category confidence: 90%
Severity confidence: 85%

Rationale: The paper discusses evaluation failures in autonomous pricing agents that can meet KPIs while violating safety constraints.

Classifier: Qwen/Qwen3.5-35B-A3B-FP8

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