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NegotiationGym: Self-Optimizing Agents in a Multi-Agent Social Simulation Environment (2510.04368v1)

Published 5 Oct 2025 in cs.MA and cs.AI

Abstract: We design and implement NegotiationGym, an API and user interface for configuring and running multi-agent social simulations focused upon negotiation and cooperation. The NegotiationGym codebase offers a user-friendly, configuration-driven API that enables easy design and customization of simulation scenarios. Agent-level utility functions encode optimization criteria for each agent, and agents can self-optimize by conducting multiple interaction rounds with other agents, observing outcomes, and modifying their strategies for future rounds.

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