Using knowledge about the opponent in game-tree search
Using knowledge about the opponent in game-tree search
Representations and solutions for game-theoretic problems
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Studies in machine cognition using the game of poker
Communications of the ACM
Poker as Testbed for AI Research
AI '98 Proceedings of the 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Incorporating opponent models into adversary search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Using probabilistic knowledge and simulation to play poker
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Game playing (invited talk): the next moves
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Machines that learn to play games
Abstracting Imperfect Information Game Trees
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
An Investigation of an Adaptive Poker Player
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Abstraction Methods for Game Theoretic Poker
CG '00 Revised Papers from the Second International Conference on Computers and Games
Learning and Exploiting Relative Weaknesses of Opponent Agents
Autonomous Agents and Multi-Agent Systems
Machine Learning
A novel approach to the placement and routing problems for field programmable gate arrays
Applied Soft Computing
Evolving explicit opponent models in game playing
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
On the usefulness of opponent modeling: the Kuhn Poker case study
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
An Experimental Approach to Online Opponent Modeling in Texas Hold'em Poker
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Using Stereotypes to Improve Early-Match Poker Play
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Opponent Modelling in Texas Hold'em Poker as the Key for Success
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Learning social preferences in games
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Particle filtering for dynamic agent modelling in simplified poker
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Gender-sensitive automated negotiators
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
GIB: imperfect information in a computationally challenging game
Journal of Artificial Intelligence Research
GIB: steps toward an expert-level bridge-playing program
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Bayesian inverse reinforcement learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Artificial Intelligence
Building a no limit texas hold'em poker agent based on game logs using supervised learning
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Exploiting adversary's risk profiles in imperfect information security games
GameSec'11 Proceedings of the Second international conference on Decision and Game Theory for Security
Game-Tree search with adaptation in stochastic imperfect-information games
CG'04 Proceedings of the 4th international conference on Computers and Games
Opponent's style modeling based on situations for bayesian poker
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Opponent modeling in texas hold'em poker
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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Poker is an interesting test-bed for artificial intelligence research. It is a game of imperfect knowledge, where multiple competing agents must deal with risk management, agent modeling, unreliable information and deception, much like decision-making applications in the real world. Agent modeling is one of the most difficult problems in decision-making applications and in poker it is essential to achieving high performance. This paper describes and evaluates Loki, a poker program capable of observing its opponents, constructing opponent models and dynamically adapting its play to best exploit patterns in the opponents' play.