449 search results - page 9 / 90 » Finding Structure in Reinforcement Learning |
NIPS
1998
14 years 11 months ago
1998
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
TSMC
2008
14 years 9 months ago
2008
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
FLAIRS
2007
14 years 12 months ago
2007
In robot navigation tasks, the representation of the surrounding world plays an important role, especially in reinforcement learning approaches. This work presents a qualitative r...
AUSAI
2005
Springer
15 years 3 months ago
2005
Springer
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
ICML
2002
IEEE
15 years 10 months ago
2002
IEEE
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...