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ICTAI
2007
IEEE
14 years 2 months ago
Multi-agent Reinforcement Learning Using Strategies and Voting
Multiagent learning attracts much attention in the past few years as it poses very challenging problems. Reinforcement Learning is an appealing solution to the problems that arise...
Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlah...
ATAL
2006
Springer
13 years 9 months ago
Can good learners always compensate for poor learners?
Can a good learner compensate for a poor learner when paired in a coordination game? Previous work has given an example where a special learning algorithm (FMQ) is capable of doin...
Keith Sullivan, Liviu Panait, Gabriel Catalin Bala...
WOSS
2004
ACM
14 years 1 months ago
Self-managed decentralised systems using K-components and collaborative reinforcement learning
Components in a decentralised system are faced with uncertainty as how to best adapt to a changing environment to maintain or optimise system performance. How can individual compo...
Jim Dowling, Vinny Cahill
FLAIRS
1998
13 years 9 months ago
Learning to Race: Experiments with a Simulated Race Car
Our focus is on designing adaptable agents for highly dynamic environments. Wehave implementeda reinforcement learning architecture as the reactive componentof a twolayer control ...
Larry D. Pyeatt, Adele E. Howe
RAS
2007
122views more  RAS 2007»
13 years 7 months ago
Developmental learning for autonomous robots
Developmental robotics is concerned with the design of algorithms that promote robot adaptation and learning through qualitative growth of behaviour and increasing levels of compe...
M. H. Lee, Q. Meng, F. Chao