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predator-prey

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Multi-Agent Deep RL meets Darwinian evolution: predator/prey agents learn under sparse reproduction-only rewards (no shaping, no cooperation signal) while heritable traits mutate and are selected across generations — a live testbed for the Baldwin effect, and for whether cooperation, defection, and free-riding emerge unassisted.

  • Updated Jul 24, 2026
  • Python

A research-grade exploration of the Tokenomics Ecological Framework, analyzing how tokens behave as predator, prey, parasite, and symbiotic species. Examines ecosystem interactions, evolutionary pressures, species population cycles, and the dynamics of economic predation, mutation, drift, and long-term survival across market cycles.

  • Updated Nov 30, 2025

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