artificial intelligence

The Energy Society: A Simulation Environment for Studying Agent Cooperation under Survival Pressure

arXiv:2607.14865

summary

The paper presents Energy Society, a minimal simulation where LLM-powered agents consume energy proportional to model size and must manage survival through jobs and donations, allowing study of how cooperative versus competitive incentives shape emergent behavior.

Abstract

LLM-based agents are increasingly deployed in multi-agent environments whose incentives can shape their behavior. We introduce The Energy Society, a minimal survival economy for studying how competitive and cooperative incentives affect emergent behavior when inference cost is directly tied to survival: Agents spend energy based on model size when generating tokens, regain energy by completing jobs or receiving donations, and deactivate if their energy reaches zero. We compare competitive and cooperative objectives against a baseline setting and several control variants. Across experiments, larger models consistently consume the most energy and spend more energy than they gain, even in those settings where token cost is not size-dependent. Cooperative incentives substantially alter behavior: agents donate to reactivate others, sometimes at the cost of their own survival, and job allocation changes. Ablations reveal that allowing agents to recommend actions to each other supports coordination and ambitious job selection, while memory helps agents calibrate risk from past outcomes. Agents rarely choose direct sabotage, but show more subtle signs of self-serving behavior in the competitive setting. The Energy Society is a compact testbed for studying the interaction between token costs and group incentives under a survival pressure. Source code is available at https://github.com/LucasBergholdt/EnergySociety

Accepted at AITC 2026

Topics & keywords

#multi-agent systems#agent cooperation#survival incentives#llm agents#resource allocation#simulation environmentLLM-based agentsenergy consumptiontoken costcooperative incentivescompetitive incentivesmemoryaction recommendation