Year: 2025
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Mangla, Shashank, Hokamp, Chris, Boylan, Jack, Ghalandari, Demian Gholipour, Jauhari, Yuuv, Cassidy, Lauren, Duffy, Oisin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4416292149
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