73 search results - page 3 / 15 » Learning multi-agent state space representations |
ICRA
2009
IEEE
14 years 24 days ago
2009
IEEE
² Similar to humans and primates, artificial creatures like robots are limited in terms of allocation of their resources to huge sensory and perceptual information. Serial process...
IJCAI
2007
13 years 7 months ago
2007
Most work on Predictive Representations of State (PSRs) has focused on learning and planning in unstructured domains (for example, those represented by flat POMDPs). This paper e...
ICML
2008
IEEE
14 years 7 months ago
2008
IEEE
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
AAAI
2006
13 years 7 months ago
2006
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto...
ICCCI
2011
Springer
12 years 5 months ago
2011
Springer
Multiagent reinforcement learning problems are especially difficult because of their dynamism and the size of joint state space. In this paper a new benchmark problem is proposed, ...