Jayd Matyas
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View article: Supported data for manuscript "Can LLM-Augmented autonomous agents cooperate?, An evaluation of their cooperative capabilities through Melting Pot"
Supported data for manuscript "Can LLM-Augmented autonomous agents cooperate?, An evaluation of their cooperative capabilities through Melting Pot" Open
The repository data corresponds partially to the manuscript titled "Can LLM-Augmented Autonomous Agents Cooperate? An Evaluation of Their Cooperative Capabilities through Melting Pot," submitted to IEEE Transactions on Artificial Intellige…
View article: Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia
Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia Open
Agent-based modeling has been around for decades, and applied widely across the social and natural sciences. The scope of this research method is now poised to grow dramatically as it absorbs the new affordances provided by Large Language …
View article: Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria Open
A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to cooperate. This is particularly critical in situations when other agents have hidden, po…
View article: Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot Open
Existing evaluation suites for multi-agent reinforcement learning (MARL) do not assess generalization to novel situations as their primary objective (unlike supervised-learning benchmarks). Our contribution, Melting Pot, is a MARL evaluati…
View article: Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot.
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. Open
Existing evaluation suites for multi-agent reinforcement learning (MARL) do not assess generalization to novel situations as their primary objective (unlike supervised-learning benchmarks). Our contribution, Melting Pot, is a MARL evaluati…