Neil Burch

发表

Rating players in games with real-valued outcomes

Christopher Archibald, Michael H. Bowling, Neil Burch, 2013, AAMAS.

DeepStack: Expert-level artificial intelligence in heads-up no-limit poker

Kevin Waugh, Michael H. Bowling, Viliam Lisý, 2017, Science.

Solving Imperfect Information Games Using Decomposition

Michael H. Bowling, Neil Burch, Michael Johanson, 2013, AAAI.

A New Algorithm for Generating Equilibria in Massive Zero-Sum Games

Michael H. Bowling, Martin Zinkevich, Neil Burch, 2007, AAAI.

Bayes' Bluff: Opponent Modelling in Poker pdf

Michael H. Bowling, Darse Billings, Finnegan Southey, 2005, UAI 2005.

Heads-up limit hold’em poker is solved

Neil Burch, Michael Johanson, Michael Bowling, 2015, Science.

Checkers Is Solved

Jonathan Schaeffer, Akihiro Kishimoto, Steve Sutphen, 2007, Science.

Approximating Game-Theoretic Optimal Strategies for Full-scale Poker

Jonathan Schaeffer, Duane Szafron, Darse Billings, 2003, IJCAI.

Solving Checkers

Jonathan Schaeffer, Akihiro Kishimoto, Steve Sutphen, 2005, IJCAI.

Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning pdf

H. Francis Song, Shimon Whiteson, Michael H. Bowling, 2018, ICML.

Solving Heads-Up Limit Texas Hold'em

Michael H. Bowling, Neil Burch, Michael Johanson, 2015, IJCAI.

No-Regret Learning in Extensive-Form Games with Imperfect Recall pdf

Michael H. Bowling, Neil Burch, Marc Lanctot, 2012, ICML.

DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker pdf

Kevin Waugh, Michael H. Bowling, Viliam Lisý, 2017, ArXiv.

Block A*: Database-Driven Search with Applications in Any-Angle Path-Planning

Jonathan Schaeffer, Robert C. Holte, Neil Burch, 2011, AAAI.

Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning

Sarah H. Cen, Eugene V. Tarassov, Jerome T. Connor, 2022, ArXiv.

Heads-up limit hold'em poker is solved

Michael H. Bowling, Michael Bradley Johanson, Neil Burch, 2017, Commun. ACM.

Rethinking Formal Models of Partially Observable Multiagent Decision Making pdf

Michael H. Bowling, Viliam Lisý, Martin Schmid, 2019, Artif. Intell..

Solving Common-Payoff Games with Approximate Policy Iteration pdf

Michael H. Bowling, Michael Bowling, Elnaz Davoodi, 2021, AAAI.

From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization pdf

Georgios Piliouras, Neil Burch, David Balduzzi, 2020, ICML.

The Hanabi Challenge: A New Frontier for AI Research

H. Francis Song, Hugo Larochelle, Marc G. Bellemare, 2019, Artif. Intell..

Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games using Baselines pdf

Michael H. Bowling, Rudolf Kadlec, Martin Schmid, 2018, AAAI.

Building the Checkers 10-piece Endgame Databases

Jonathan Schaeffer, Steve Sutphen, Robert Lake, 2003, ACG.

AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games pdf

Michael H. Bowling, Martin Schmid, Matej Moravcik, 2016, AAAI.

Game-Tree Search with Adaptation in Stochastic Imperfect-Information Games

Jonathan Schaeffer, Michael H. Bowling, Darse Billings, 2004, Computers and Games.

Mastering the game of Stratego with model-free multiagent reinforcement learning

Sarah H. Cen, Jerome T. Connor, L. Sifre, 2022, Science.

Revisiting CFR+ and Alternating Updates

Martin Schmid, Matej Moravcik, Neil Burch, 2018, J. Artif. Intell. Res..

Time and Space: Why Imperfect Information Games are Hard

Neil Burch, Neil Burch, 2018 .

Memory-Based Heuristics for Explicit State Spaces

Nathan R. Sturtevant, Jonathan Schaeffer, Ariel Felner, 2009, IJCAI.

Automatic move pruning for single-agent search

Robert C. Holte, Neil Burch, R. Holte, 2014, AI Commun..

Predicting the Performance of IDA* with Conditional Distributions

Ariel Felner, Robert C. Holte, Neil Burch, 2008, AAAI.

Player of Games pdf

Kevin Waugh, Michael H. Bowling, Rudolf Kadlec, 2021, ArXiv.

Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions

Duane Szafron, Neil Burch, Marc Lanctot, 2012, NIPS.

Using Response Functions to Measure Strategy Strength

Michael H. Bowling, Neil Burch, Trevor Davis, 2014, AAAI.

Generalized Sampling and Variance in Counterfactual Regret Minimization

Duane Szafron, Michael H. Bowling, Neil Burch, 2012, AAAI.

Sound Search in Imperfect Information Games pdf

Michael H. Bowling, Neil Burch, Marc Lanctot, 2020, ArXiv.

Finding Optimal Abstract Strategies in Extensive-Form Games

Michael H. Bowling, Neil Burch, Nolan Bard, 2012, AAAI.

Strategy evaluation in extensive games with importance sampling

Duane Szafron, Michael H. Bowling, Neil Burch, 2008, ICML '08.

Online implicit agent modelling

Michael H. Bowling, Neil Burch, Nolan Bard, 2013, AAMAS.

Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning

Marc Lanctot, J. Pérolat, Thomas W. Anthony, 2023, ArXiv.

Evaluating state-space abstractions in extensive-form games

Michael H. Bowling, Richard Anthony Valenzano, Neil Burch, 2013, AAMAS.

Automatic Move Pruning Revisited

Robert C. Holte, Neil Burch, R. Holte, 2021, SOCS.

Predicting the Performance of IDA* using Conditional Distributions

Ariel Felner, Robert C. Holte, Neil Burch, 2014, J. Artif. Intell. Res..

DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker

Michael Bradley Johanson, Michael Bowling, Nolan Bard, 2017, ArXiv.