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JCP
2008
139views more  JCP 2008»
13 years 7 months ago
Agent Learning in Relational Domains based on Logical MDPs with Negation
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
Song Zhiwei, Chen Xiaoping, Cong Shuang
FLAIRS
2004
13 years 9 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
DLT
2006
13 years 9 months ago
Can Abstract State Machines Be Useful in Language Theory?
ract State Machines Be Useful in Language Theory? Yuri Gurevich a Margus Veanes a Charles Wallace b aMicrosoft Research, Redmond, Washington, USA bMichigan Tech, Houghton, Michigan...
Yuri Gurevich, Charles Wallace
FORTE
1997
13 years 9 months ago
Automatic Checking of Aggregation Abstractions Through State Enumeration
c Checking of Aggregation Abstractions Through State Enumeration Seungjoon Park, Member, IEEE, Satyaki Das, and David L. Dill, Member, IEEE —Aggregation abstraction is a way of d...
Seungjoon Park, Satyaki Das, David L. Dill
ASM
2005
ASM
14 years 1 months ago
RAM Simulation of BGS Model of Abstract State Machines
lation of BGS model of Abstract State Machines Comandur Seshadhri1 , Anil Seth2 , and Somenath Biswas2 1 Department of Computer Science Princeton University, Princeton NJ 08544, US...
Seshadhri Comandur, Anil Seth, Somenath Biswas