64 search results - page 3 / 13 » Reducing the complexity of multiagent reinforcement learning |
ATAL
2010
Springer
13 years 6 months ago
2010
Springer
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
AAAI
2010
13 years 6 months ago
2010
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
ATAL
2006
Springer
13 years 9 months ago
2006
Springer
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
ICANN
2010
Springer
13 years 5 months ago
2010
Springer
We propose a data structure that decreases complexity of unsupervised competitive learning algorithms which are based on the growing cells structures approach. The idea is based on...
ICARCV
2006
IEEE
13 years 11 months ago
2006
IEEE
— Multi-agent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, etc. Learning approaches to multi-ag...