85 search results - page 9 / 17 » Markov Games as a Framework for Multi-Agent Reinforcement Le... |
ATAL
2005
Springer
14 years 1 months ago
2005
Springer
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...
PPSN
2004
Springer
14 years 26 days ago
2004
Springer
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
AI
2002
Springer
13 years 7 months ago
2002
Springer
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 ...
KDD
2010
ACM
13 years 11 months ago
2010
ACM
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...