23 search results - page 1 / 5 » Combining Stochastic Task Models with Reinforcement Learning... |
AIPS
2006
13 years 6 months ago
2006
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
NIPS
2001
13 years 6 months ago
2001
We consider the problem of learning to attain multiple goals in a dynamic environment, which is initially unknown. In addition, the environment may contain arbitrarily varying ele...
HCW
1999
IEEE
13 years 9 months ago
1999
IEEE
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
CIIA
2009
13 years 6 months ago
2009
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
IAT
2008
IEEE
13 years 11 months ago
2008
IEEE
This paper extends the link between evolutionary game theory and multi-agent reinforcement learning to multistate games. In previous work, we introduced piecewise replicator dynam...