CIG 2005 - PDF Preprint Papers

CIG 2005 IEEE Symposium on Computational Intelligence and Games

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CIG
2005
IEEE

195views Applied Computing» more CIG 2005»

Monte Carlo Planning in RTS Games

13 years 6 months ago

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Abstract- Monte Carlo simulations have been successfully used in classic turn–based games such as backgammon, bridge, poker, and Scrabble. In this paper, we apply the ideas to th...

Michael Chung, Michael Buro, Jonathan Schaeffer

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Id	Views	Title	Status

1	195	Monte Carlo Planning in RTS Games	claim
2	181	Further Evolution of a Self-Learning Chess Program	claim
3	169	Building Reactive Characters for Dynamic Gaming Environments	claim
4	169	How to Protect Peer-to-Peer Online Games from Cheats	claim
5	162	Nannon: A Nano Backgammon for Machine Learning Research	claim
6	159	Case-Injection Improves Response Time for a Real-Time Strategy Game	claim
7	151	Board Evaluation For The Virus Game	claim
8	145	Evolving a Neural Network Location Evaluator to Play Ms. Pac-Man	claim
9	142	Coevolution in Hierarchical AI for Strategy Games	claim
10	139	Bayesian Generation and Integration of K-nearest-neighbor Patterns for 19x19 Go	claim
11	139	Forcing Neurocontrollers to Exploit Sensory Symmetry Through Hard-wired Modularity in the Game of Cellz	claim
12	134	Combining Coaching and Learning to Create Cooperative Character Behavior	claim
13	132	On TRACS: Dealing with a Deck of Double-Sided Cards	claim
14	131	A Survey on Multiagent Reinforcement Learning Towards Multi-Robot Systems	claim
15	122	Synchronous and Asynchronous Network Evolution in a Population of Stubborn Prisoners	claim
16	121	Co-evolutionary Strategies for an Alternating-Offer Bargaining Problem	claim
17	120	Adapting Reinforcement Learning for Computer Games: Using Group Utility Functions	claim
18	112	Dealing with Parameterized Actions in Behavior Testing of Commercial Computer Games	claim
19	108	Evolving Reactive NPCs for the Real-Time Simulation Game	claim
20	98	A Hybrid AI System for Agent Adaptation in a First Person Shooter	claim
21	98	Adaptive Strategies of MTD-f for Actual Games	claim
22	96	Combining Tactical Search and Monte-Carlo in the Game of Go	claim
23	95	Similarity-based Opponent Modelling using Imperfect Domain Theories	claim
24	92	Pared-down Poker: Cutting to the Core of Command and Control	claim
25	90	A Generic Approach for Generating Interesting Interactive Pac-Man Opponents	claim
26	89	Designing and Implementing E-market Games	claim
27	78	Incrementally Learned Subjectivist Probabilities in Games	claim
28	72	Utile Coordination: Learning Interdependencies Among Cooperative Agents	claim
29	69	An Evolutionary Approach to Strategies for the Game of Monopoly	claim

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