Predictive Allostatic Organization in Recurrent and Spiking Agents Under Partial Observability
Adaptive behavior under partial observability depends on internal organization that carries information beyond the current observation. Drawing on Barrett and Miller's account of categorization as predictive, compressive, functionally organized, and allostatically constrained, we test whether recurrent and spiking agents develop internal states with corresponding computational properties. Agents operate in an energy-constrained foraging task requiring resource acquisition, threat avoidance, contact-dependent consumption, and regulation of an internal energy variable. In a frozen benchmark, learned agents outperform random and heuristic baselines; the trace-augmented recurrent policy is st...
| Authors | Frederick Hayes |
|---|---|
| Primary category | cs.NE |
| Published | 11 August 2026 |
| Last updated at source | 11 August 2026 |
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