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AI
2002
Springer
15 years 6 months ago
Multiagent learning using a variable learning rate
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Michael H. Bowling, Manuela M. Veloso
ROMAN
2007
IEEE
173views Robotics» more  ROMAN 2007»
16 years 19 days ago
Human-Robot Interactions as a Cognitive Catalyst for the Learning of Behavioral Attractors
— We address in this paper the problem of the autonomous online learning of a sensory-motor task, demonstrated by an operator guiding the robot. For the last decade, we have deve...
Christophe Giovannangeli, Philippe Gaussier
154
Voted
AAMAS
2005
Springer
15 years 12 months ago
Learning to Coordinate Using Commitment Sequences in Cooperative Multi-agent Systems
We report on an investigation of the learning of coordination in cooperative multi-agent systems. Specifically, we study solutions that are applicable to independent agents i.e. ...
Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. ...
ICML
1994
IEEE
15 years 10 months ago
Markov Games as a Framework for Multi-Agent Reinforcement Learning
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
Michael L. Littman
IFIP3
2003
114views Education» more  IFIP3 2003»
15 years 7 months ago
Enabling Postgraduate Learning in the Workplace
: This paper describes a research project that was carried out to determine and evaluate the learning environment customisations required to support selfmotivated, able, and experi...
Nicola Beasley, John A. Ford, Nils Tomes