Who's Who of AI

Chris Amato

122 trust researcher @cjdamato.bsky.social · 1,807 followers
Agents & robotics AI research Culture, work & education
Why they matter

Researcher with public evidence across Agents & robotics, AI research, Culture, work & education.

AI signals
2
past 30d
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distinct domains
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past 30d
Latest signal
11d ago
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Associate Professor at Northeastern University and father of 3. Interests include artificial intelligence, reinforcement learning, and robotics (he/him).
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Articles & links

A new version of my book on cooperative multi-agent reinforcement learning is now available. A longer version will eventually be published with Frans Oliehoek so let us know your thoughts! arxiv.org/abs/2405.06161

An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning arxiv.org
AI Weekly's analysis →
  • Amato organizes cooperative MARL around three settings: centralized training and execution, centralized training for decentralized execution, and decentralized training and execution.
  • The paper walks through independent Q-learning, value factorization methods VDN, QMIX and QPLEX, and centralized critic methods MADDPG, COMA and MAPPO.
  • Amato writes that CTDE is the most common paradigm because it leverages centralized information at training while keeping execution decentralized.
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View on Bluesky · ♥ 26 ↻ 3 ↩ 1 · 2 from the directory shared this · 11d ago
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