PhD Proposal: Multi-Agent Autonomous Decision Making in Artificial Intelligence

Abstract:

Multi-Agent Autonomous Decision Making, especially Multi-Agent Reinforcement Learning (MARL), is an emerging area of Artificial Intelligence (AI) where autonomous agents interact with each other, fostering competition and/or cooperation in real world problems like climate change, supply chains, self-driving cars, sports, interdiction games, war games among other uses.The PhD proposal has been arranged considering the research works already carried out and published and those are continuing in the areas of AI Alignment and Social Cooperation of Autonomous AI Agents, Speedup and Scalability for Efficient Multi-Agent AI, Multi-Agent Explainable AI and Unlearning to Build Trustworthy AI and Real World Applications of Multi-Agent AI for Climate Conservation, Global Supply Chain orchestration etc.

Examining Committee

Chair:

Dr. John Dickerson

Department Representative:

Dr. Tom Goldstein

Members:

Dr. Hal Daumé