publication . Doctoral thesis . 2006

Behavior acquisition in artificial agents

Thurau, Christian;
Open Access English
  • Published: 01 Jan 2006
  • Publisher: Bielefeld University
  • Country: Germany
Abstract
Computational skill acquisition in robots and simulated agents has been a topic of increasing popularity throughout the last years. Despite impressive progress, autonomous behavior at a level of animals and humans are not yet replicated by machines. Especially when a complex environment demands versatile, goal-oriented behavior, current artificial systems show shortcomings. Consider for instance modern 3D computer games. Despite their key role for more emersive game experience, surprisingly little effort was made towards new techniques for life-like behavior creation in artificial characters. Modern interactive computer games provide the ability to objectively r...
Subjects
free text keywords: Game AI, Machine learning, Behavior acquisition, Computerspiel, Mustererkennung, Imitation learning, Behavior modeling, Autonomer Agent, Maschinelles Lernen, Data Mining, Turing-Test, ddc:004
Related Organizations

D. Higgins. AI Game Programming Wisdom, chapter Pathfinding Design Architecture, pages 122-132. Charles River Media, 2002c.

R.A. Jacobs, M.I. Jordan, S.J. Nowlan, and G.E. Hinton. Adaptive Mixture of Local Experts. Neural Computation, 3(1):79-87, 1991.

J. Orkin. AI Game Programming Wisdom 2, chapter Applying Goal-Oriented Action Planning to Games, pages 217-227. Charles River Media, 2004.

G. N. Yannakakis and J. Hallam. Evolving Opponents for Interesting Interactive Computer Games. In Proc. 8th Int. Conf. on the Simulation of Adaptive Behavior (SAB'04), pages 499-508, 2004. [OpenAIRE]

Abstract
Computational skill acquisition in robots and simulated agents has been a topic of increasing popularity throughout the last years. Despite impressive progress, autonomous behavior at a level of animals and humans are not yet replicated by machines. Especially when a complex environment demands versatile, goal-oriented behavior, current artificial systems show shortcomings. Consider for instance modern 3D computer games. Despite their key role for more emersive game experience, surprisingly little effort was made towards new techniques for life-like behavior creation in artificial characters. Modern interactive computer games provide the ability to objectively r...
Subjects
free text keywords: Game AI, Machine learning, Behavior acquisition, Computerspiel, Mustererkennung, Imitation learning, Behavior modeling, Autonomer Agent, Maschinelles Lernen, Data Mining, Turing-Test, ddc:004
Related Organizations

D. Higgins. AI Game Programming Wisdom, chapter Pathfinding Design Architecture, pages 122-132. Charles River Media, 2002c.

R.A. Jacobs, M.I. Jordan, S.J. Nowlan, and G.E. Hinton. Adaptive Mixture of Local Experts. Neural Computation, 3(1):79-87, 1991.

J. Orkin. AI Game Programming Wisdom 2, chapter Applying Goal-Oriented Action Planning to Games, pages 217-227. Charles River Media, 2004.

G. N. Yannakakis and J. Hallam. Evolving Opponents for Interesting Interactive Computer Games. In Proc. 8th Int. Conf. on the Simulation of Adaptive Behavior (SAB'04), pages 499-508, 2004. [OpenAIRE]

Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue