ABSTRACT
It has been an open challenge for self-interested agents to make optimal sequential decisions in complex multi-agent systems, where agents might achieve higher utility via collaboration. The Microsoft Malmo Collaborative AI Challenge (MCAC), which is designed to encourage research relating to various problems in Collaborative AI, takes the form of a Minecraft mini-game where players might work together to catch a pig or deviate from cooperation, for pursuing high scores to win the challenge. Various characteristics, such as complex interactions among agents, uncertainties, sequential decision making and limited learning trials all make it extremely challenging to find effective strategies. This talk presents HogRider – the champion agent of MCAC in 2017 out of 81 teams from 26 countries. One key innovation of HogRider is a generalized agent type hypothesis framework to identify the behavior model of the other agents. On top of that, a second key innovation is a novel Q-learning approach combing ideas such as state-action abstraction to reduce problem scale, a warm start approach using human reasoning for addressing limited learning trials, and an active greedy strategy to balance exploitation-exploration. This talk will also outline future research directions.
BIO
Dr. Bo An is a Nanyang Assistant Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He received his PhD in Computer Science from the University of Massachusetts, Amherst. His current research interests include artificial intelligence, multiagent systems, game theory, and optimization. He has published over 70 referred papers at AAMAS, IJCAI, AAAI, ICAPS, KDD, JAAMAS, AIJ and ACM/IEEE Transactions. Dr. An was the recipient of the 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award, an Operational Excellence Award from the Commander, First Coast Guard District of the United States, the Best Innovative Application Paper Award at AAMAS’12, the 2012 INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice, and the Innovative Application Award at IAAI’16. He was invited to give the Early Career Spotlight talk at IJCAI’17. He led the HogRider team, which won the 2017 Microsoft Collaborative AI Challenge. He is a member of the editorial board of JAIR and the Associate Editor of JAAMAS. He was elected to the Board of Directors of IFAAMAS.
