1176 search results - page 5 / 236 » Sparse reward processes |
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
ICML
2001
IEEE
15 years 10 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
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AAAI
2006
14 years 11 months ago
2006
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
DSN
2008
IEEE
15 years 4 months ago
2008
IEEE
Embedded systems for closed-loop applications often behave as discrete-time semi-Markov processes (DTSMPs). Performability measures most meaningful to iterative embedded systems, ...
MASCOTS
1996
14 years 10 months ago
1996
Formalisms based on stochastic Petri Nets (SPNs) can employ structural analysis to ensure that the underlying stochastic process is fully determined. The focus is on the detection...