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ATAL
2005
Springer
14 years 6 months ago
Automatic computer game balancing: a reinforcement learning approach
Designing agents whose behavior challenges human players adequately is a key issue in computer games development. This work presents a novel technique, based on reinforcement lear...
Gustavo Andrade, Geber Ramalho, Hugo Santana, Vinc...
SAC
2005
ACM
14 years 6 months ago
Reinforcement learning agents with primary knowledge designed by analytic hierarchy process
This paper presents a novel model of reinforcement learning agents. A feature of our learning agent model is to integrate analytic hierarchy process (AHP) into a standard reinforc...
Kengo Katayama, Takahiro Koshiishi, Hiroyuki Narih...
KCAP
2005
ACM
14 years 6 months ago
Knowledge transfer via advice taking
We present a framework for knowledge transfer from one reinforcement learning task to a related task through advicetaking mechanisms. We discuss the importance of transfer in comp...
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richa...
CIG
2005
IEEE
14 years 6 months ago
Adapting Reinforcement Learning for Computer Games: Using Group Utility Functions
AbstractGroup utility functions are an extension of the common team utility function for providing multiple agents with a common reinforcement learning signal for learning cooperat...
Jay Bradley, Gillian Hayes
IROS
2006
IEEE
190views Robotics» more  IROS 2006»
14 years 6 months ago
Q-RAN: A Constructive Reinforcement Learning Approach for Robot Behavior Learning
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
Jun Li, Achim J. Lilienthal, Tomás Mart&iac...
IROS
2006
IEEE
187views Robotics» more  IROS 2006»
14 years 6 months ago
Fast and Stable Learning of Quasi-Passive Dynamic Walking by an Unstable Biped Robot based on Off-Policy Natural Actor-Critic
— Recently, many researchers on humanoid robotics are interested in Quasi-Passive-Dynamic Walking (Quasi-PDW) which is similar to human walking. It is desirable that control para...
Tsuyoshi Ueno, Yutaka Nakamura, Takashi Takuma, To...
IJCNN
2006
IEEE
14 years 6 months ago
Reinforcement Learning for Parameterized Motor Primitives
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
Jan Peters, Stefan Schaal
ICARCV
2006
IEEE
100views Robotics» more  ICARCV 2006»
14 years 6 months ago
Decentralized Reinforcement Learning Control of a Robotic Manipulator
— Multi-agent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, etc. Learning approaches to multi-ag...
Lucian Busoniu, Bart De Schutter, Robert Babuska
CIMCA
2006
IEEE
14 years 6 months ago
Model-driven Walks for Resource Discovery in Peer-to-Peer Networks
In this paper, a distributed and adaptive approach for resource discovery in peer-to-peer networks is presented. This approach is based on the mobile agent paradigm and the random...
Mohamed Bakhouya, Jaafar Gaber
CIG
2006
IEEE
14 years 6 months ago
Monte-Carlo Go Reinforcement Learning Experiments
Abstract— This paper describes experiments using reinforcement learning techniques to compute pattern urgencies used during simulations performed in a Monte-Carlo Go architecture...
Bruno Bouzy, Guillaume Chaslot