SOURCE-LINKED INTELLIGENCE
Evolutionary Recurrent Decision Model in Developing Adaptive and Maladaptive Behaviors
This study introduces the evolutionarily recurrent decision model (ERDM), a computational reinforcement learning framework designed to examine how evolutionary mismatch, bounded rationality, and satisficing contribute to adaptive and maladaptive behavior. ERDM simulates agents across evolutionary recurrent environments, including threat, prey/goal-pursuits, and alliances. Agents learn through competing rewards abstracted from survival metrics. A validity study under varying adverse childhood experiences demonstrates that distinct adaptive and maladaptive strategies, such as learned helplessnes
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T00:45:05.000Z
First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.