Michael Bradley Johanson

Artificial Intelligence · 2007–2017

A researcher in the Science corpus: 11 papers; trusts 15 researchers and is trusted by 56 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it; #2,788 of 35,345 by trust here, #3,703 by citations
• Game & Decision Theory — 27 citations into it; #13 of 249 by trust here, #18 by citations
• Reinforcement Learning — 20 citations into it; #1,665 of 2,242 by trust here, #632 by citations
• Management Science and Operations Research — 17 citations into it; #727 of 11,946 by trust here, #1,045 by citations
• Optimization & Training — 8 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Michael Bradley Johanson trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Martin A. Zinkevich
2. Kevin Waugh
3. Michael H. Bowling
4. Andrew Gilpin
5. Tuomas Sandholm
6. Charles Peter Elkan
7. Neil Burch
8. Darse Billings
9. Samid Hoda
10. Marc Lanctot

Who trusts Michael Bradley Johanson overall

1. Neil Burch
2. Noam Brown
3. Tuomas Sandholm
4. Johannes Heinrich
5. Sam Ganzfried
6. Marc Lanctot
7. Michael H. Bowling
8. David Silver
9. Kevin Waugh
10. Dustin Morrill

Papers from Michael Bradley Johanson's perspective

Ordered by how strongly the researchers Michael Bradley Johanson trusts endorse each paper. Same corpus, a different order for every researcher.

1. A Course in Game Theory
2. ImageNet classification with deep convolutional neural networks
3. Temporal Difference Learning and TD-Gammon
4. The challenge of poker
5. A Competitive Texas Hold'em Poker Player via Automated Abstraction and Real-Time Equilibrium Computation
6. Approximating game-theoretic optimal strategies for full-scale poker
7. Regret Minimization in Games with Incomplete Information
8. Monte Carlo Sampling for Regret Minimization in Extensive Games
9. Excessive Gap Technique in Nonsmooth Convex Minimization (SIAM Journal on Optimization)
10. Measuring the Size of Large No-Limit Poker Games

Their papers

• DeepStack: Expert-level artificial intelligence in heads-up no-limit poker (2017) — 1,018 citations
• Regret Minimization in Games with Incomplete Information (2007) — 899 citations
• Heads-up limit hold’em poker is solved (2015) — 554 citations
• Solving Imperfect Information Games Using Decomposition (2013) — 121 citations
• Measuring the Size of Large No-Limit Poker Games (2013) — 84 citations
• Finding Optimal Abstract Strategies in Extensive-Form Games (2012) — 85 citations
• DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker (2017) — 225 citations
• Solving Heads-Up Limit Texas Hold'em (2015) — 182 citations
• Evaluating state-space abstractions in extensive-form games (2013) — 81 citations
• Accelerating Best Response Calculation in Large Extensive Games (2011)
• A Practical Use of Imperfect Recall (2009) — 80 citations