Why does a maladaptive chronic pain perception outperform normal pain in non-stationary environments?

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• The chronic pain model outperforms the normal pain model in non-stationary environments despite producing negative well-beingclaim0.852
  Surprising finding that maladaptive perception can yield superior task performance in changing environments
• Chronic pain agent accumulates negative cumulative well-being across its entire lifetime in non-stationary environmentfinding0.765
  Key behavioral signature of chronic model paralleling human chronic pain experience
• Introspective agents generally outperform standard no-pain baseline agents across environments and reward categoriesclaim0.745
  Central empirical claim of the paper supported by statistical tests
• "Pain is a core component of adaptive learning...signals that encode internal evaluations that guide the agent through complex environments."quote0.745
  Load-bearing motivation for using pain as a learning signal in the computational framework
• The chronic agent's high performance despite negative well-being aligns with findings on chronic pain and quality of life in humansclaim0.742
  Cross-domain interpretive claim linking computational results to human chronic pain literature
• Normal pain agent maintains mostly positive cumulative well-being and recovers before finding food after changefinding0.739
  Contrasts with chronic agent; normal model provides stable exploration bonus without addiction-like dynamics
• Chronic Pain Perception Modelframework0.738
  HMM parameterization with sticky transitions and ambiguous emissions representing maladaptive pain perception
• Chronic pain agent achieves M=4235.5, SD=180.3 COR in non-stationary All category (n=300), highest across all chronic resultsfinding0.737
  Peak performance of chronic pain agents across all reward categories in non-stationary environment