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Found 22 papers, 1 papers with code
Nonparametric Strategy Test
The results from both tests are combined using Bonferroni correction to produce a complete test for a given significance level $\alpha.$ We applied the test to publicly available data of human rock-paper-scissors play.
Bayesian Opponent Modeling in Multiplayer Imperfect-Information Games
In many real-world settings agents engage in strategic interactions with multiple opposing agents who can employ a wide variety of strategies.
Observable Perfect Equilibrium
While Nash equilibrium has emerged as the central game-theoretic solution concept, many important games contain several Nash equilibria and we must determine how to select between them in order to create real strategic agents.
Fictitious Play with Maximin Initialization
Fictitious play has recently emerged as the most accurate scalable algorithm for approximating Nash equilibrium strategies in multiplayer games.
Safe Equilibrium
The standard game-theoretic solution concept, Nash equilibrium, assumes that all players behave rationally.
Human strategic decision making in parametrized games
Often the decisions must be made by a human under time and resource constraints, and it is unrealistic to assume that a human can solve the game in real time.
Computing Nash Equilibria in Multiplayer DAG-Structured Stochastic Games with Persistent Imperfect Information
Many important real-world settings contain multiple players interacting over an unknown duration with probabilistic state transitions, and are naturally modeled as stochastic games.
Algorithm for Computing Approximate Nash Equilibrium in Continuous Games with Application to Continuous Blotto
We present a new algorithm for {approximating} Nash equilibrium strategies in continuous games.
Prediction of Bayesian Intervals for Tropical Storms
Building on recent research for prediction of hurricane trajectories using recurrent neural networks (RNNs), we have developed improved methods and generalized the approach to predict Bayesian intervals in addition to simple point estimates.
Fast Complete Algorithm for Multiplayer Nash Equilibrium
We describe a new complete algorithm for computing Nash equilibrium in multiplayer general-sum games, based on a quadratically-constrained feasibility program formulation.
Empirical Analysis of Fictitious Play for Nash Equilibrium Computation in Multiplayer Games
While fictitious play is guaranteed to converge to Nash equilibrium in certain game classes, such as two-player zero-sum games, it is not guaranteed to converge in non-zero-sum and multiplayer games.
Parallel Algorithm for Approximating Nash Equilibrium in Multiplayer Stochastic Games with Application to Naval Strategic Planning
Many real-world domains contain multiple agents behaving strategically with probabilistic transitions and uncertain (potentially infinite) duration.
Most Important Fundamental Rule of Poker Strategy
Poker is a large complex game of imperfect information, which has been singled out as a major AI challenge problem.
Successful Nash Equilibrium Agent for a 3-Player Imperfect-Information Game
Creating strong agents for games with more than two players is a major open problem in AI.
Optimization-Based Algorithm for Evolutionarily Stable Strategies against Pure Mutations
It turns out that the vast majority of the games included in the experiments contain ESS with small support, and our algorithm is outperformed by a support-enumeration based approach.
Predicting Hurricane Trajectories using a Recurrent Neural Network
We utilized their latitude, longitude, wind speed, and pressure publicly provided by the National Hurricane Center (NHC) to predict the trajectory of a hurricane at 6-hour intervals.
Optimal Weighting for Exam Composition
A problem faced by many instructors is that of designing exams that accurately assess the abilities of the students.
Computing Human-Understandable Strategies
Algorithms for equilibrium computation generally make no attempt to ensure that the computed strategies are understandable by humans.
Optimal Number of Choices in Rating Contexts
We study the problem of understanding when using a different number of options is optimal.
Bayesian Opponent Exploitation in Imperfect-Information Games
The natural setting for opponent exploitation is the Bayesian setting where we have a prior model that is integrated with observations to create a posterior opponent model that we respond to.
My Reflections on the First Man vs. Machine No-Limit Texas Hold 'em Competition
The first ever human vs. computer no-limit Texas hold 'em competition took place from April 24-May 8, 2015 at River's Casino in Pittsburgh, PA.
Computing Strong Game-Theoretic Strategies in Jotto
We develop a new approach that computes approximate equilibrium strategies in Jotto, a popular word game.
