6 search results - page 1 / 2 » Reinforcement Learning for Agents with Many Sensors and Actu... |
CORR
2011
Springer
12 years 8 months ago
2011
Springer
In this paper, we confront the problem of applying reinforcement learning to agents that perceive the environment through many sensors and that can perform parallel actions using ...
AAAI
2011
12 years 4 months ago
2011
In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND...
EUROCAST
2007
Springer
13 years 11 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
ATAL
2008
Springer
13 years 6 months ago
2008
Springer
Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
IJCAI
2001
13 years 6 months ago
2001
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...