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ENTCS
2006
134views more  ENTCS 2006»
13 years 10 months ago
Partial Order Reduction for Probabilistic Branching Time
In the past, partial order reduction has been used successfully to combat the state explosion problem in the context of model checking for non-probabilistic systems. For both line...
Christel Baier, Pedro R. D'Argenio, Marcus Grö...
DATE
2008
IEEE
136views Hardware» more  DATE 2008»
14 years 4 months ago
A Framework of Stochastic Power Management Using Hidden Markov Model
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
Ying Tan, Qinru Qiu
NIPS
2004
13 years 11 months ago
Learning first-order Markov models for control
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
Pieter Abbeel, Andrew Y. Ng
ATAL
2006
Springer
14 years 1 months ago
On the relationship between MDPs and the BDI architecture
In this paper we describe the initial results of an investigation into the relationship between Markov Decision Processes (MDPs) and Belief-Desire-Intention (BDI) architectures. W...
Gerardo I. Simari, Simon Parsons
CORR
2010
Springer
105views Education» more  CORR 2010»
13 years 8 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...