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» Interacting Abstract State Machines
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AUSAI
1999
Springer
15 years 2 months ago
Q-Learning in Continuous State and Action Spaces
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...
ICML
2002
IEEE
15 years 10 months ago
Discovering Hierarchy in Reinforcement Learning with HEXQ
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...
Bernhard Hengst
IPSN
2004
Springer
15 years 3 months ago
Distributed state representation for tracking problems in sensor networks
This paper investigates the problem of designing decentralized representations to support monitoring and inferences in sensor networks. State-space models of physical phenomena su...
Juan Liu, Maurice Chu, Jie Liu, Jim Reich, Feng Zh...
ASM
2003
ASM
15 years 3 months ago
ASMs versus Natural Semantics: A Comparison with New Insights
Abstract. We compare three specification frameworks for the operationtics of programming languages, abstract state machines (ASMs) and the two incarnations of natural semantics, b...
Sabine Glesner
DNA
2005
Springer
102views Bioinformatics» more  DNA 2005»
15 years 3 months ago
Chain Reaction Systems Based on Loop Dissociation of DNA
In the field of DNA computing, more and more efforts are made for constructing molecular machines made of DNA that work in vitro or in vivo. States of some of those machines are...
Keiichiro Takahashi, Satsuki Yaegashi, Atsushi Kam...