Neil Burch
Fellow & Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Fellow & Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Working in large, sometimes ambiguous environments, Neil seeks to make search applicable to a wider class of imperfect information environments.
Neil Burch’s research centres around imperfect information games – ones in which different information is known to each player – and improving the use of search techniques in large environments. Working in these large, sometimes ambiguous environments, he seeks to make search applicable to a wider class of imperfect information environments and remove limitations and assumptions in current search procedures. Through this research, Neil is working to develop methods for AI agents to use search for decision making without requiring the agent to consider all possible worlds. He is also focused on combining learning and search, using imperfect information settings as opportunities to learn more about other agents. Combining these two research lines, Neil aims to expand our ability to use search in large, real-world settings where actors have different observations of the world, and may not all be making perfectly-rational decisions.
Neil is a Fellow and Canada CIFAR AI Chair at Amii, an Adjunct Professor in the Department of Computing Science at the University of Alberta, and a Senior Research Scientist with Sony AI. He has acted as co-chair for the Annual Computer Poker Competition, where he was a part of the team that achieved first place in 24 out of 44 events (top 3 in 40 events). Throughout his career, Neil has made significant contributions to the area of games research, including his involvement in solving checkers in 2007 and heads-up limit poker in 2015 and in producing DeepStack, the first AI system to beat human professionals at heads-up no-limit poker in 2016. His research has appeared on the cover of Science magazine and been featured in top conferences, including the Association for the Advancement of Artificial Intelligence Conference on AI, the International Joint Conference on Artificial Intelligence (IJCAI), the Neural Information Processing Systems Conference, and many others. He has won best paper awards at IJCAI for his work in both poker as well as checkers.
Mar 1st 2020
Research Post
Feb 21st 2017
Research Post
Jul 19th 2019
Research Post
Neil has won best paper awards at the International Joint Conference on Artificial Intelligence both for his work on poker as well as checkers.
Feb 1st 2022
Research Post
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chairs Neil Burch and Michael Bowling: Rethinking formal models of partially observable multiagent decision making
Jan 21st 2022
News
AI has transformed the world of professional poker. Discover how the work of Amii researchers contributed to pro players going all-in on machine learning.
Dec 6th 2021
Research Post
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chairs Neil Burch and Micheal Bowling: Player of Games
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