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» Learning Character Behaviors Using Agent Modeling in Games
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CEC
2010
IEEE
15 years 23 days ago
Learning to overtake in TORCS using simple reinforcement learning
In modern racing games programming non-player characters with believable and sophisticated behaviors is getting increasingly challenging. Recently, several works in the literature ...
Daniele Loiacono, Alessandro Prete, Pier Luca Lanz...
PAMI
2007
186views more  PAMI 2007»
14 years 11 months ago
Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
Jesse Hoey, James J. Little
ACMACE
2007
ACM
15 years 3 months ago
Motivated reinforcement learning for adaptive characters in open-ended simulation games
Recently a new generation of virtual worlds has emerged in which users are provided with open-ended modelling tools with which they can create and modify world content. The result...
Kathryn Elizabeth Merrick, Mary Lou Maher
AAI
2005
93views more  AAI 2005»
14 years 11 months ago
Learning By Feeling: Evoking Empathy With Synthetic Characters
Virtual environments are now becoming a promising new technology to be used in the development of interactive learning environments for children. Perhaps triggered by the success ...
Ana Paiva, João Dias, Daniel Sobral, Ruth A...
AAMAS
2007
Springer
15 years 5 months ago
Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...