Karlsruhe brainstormers - Design principles

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1856, Issue , 2000, Pages 588-591

  Riedmiller, M ^a   Buck, S ^a   Merke, A ^a   Ehrmann, R ^a   Thate, O ^a   Dilger, S ^a   Sinner, A ^a   Hofmann, A ^a   Frommberger, L ^a  

^a UNIVERSITY OF KARLSRUHE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; SPORTS;

DESIGN PRINCIPLES; REINFORCEMENT LEARNING TECHNIQUES; ROBOCUP; RULE BASED; STOCKHOLM;

REINFORCEMENT LEARNING;

EID: 84944885305     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45327-x_57     Document Type: Conference Paper

References (4)

1. A. G. Barto, S. J. Bradtke, and S. P. Singh. Learning to act using real-time dynamic programming. Artificial Intelligence, (72): 81-138, 1995.
2. M. Riedmiller. Concepts and facilities of a neural reinforcement learning control architecture for technical process control. Neural Computing and Application, 1999.
3. P. Stone and M. Veloso. Team-partitioned, opaque-transition reinforcement learning. In M. Asada and H. Kitano, RoboCup-98: Robot Soccer World Cup II.
4. R. S. Sutton, D. Precup, and S. Singh. Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 1999. to appear.