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SIGSOFT
2009
ACM
14 years 8 months ago
Automatic steering of behavioral model inference
Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and timecons...
David Lo, Leonardo Mariani, Mauro Pezzè
ITS
2000
Springer
137views Multimedia» more  ITS 2000»
13 years 11 months ago
Design Principles for a System to Teach Problem Solving by Modelling
This paper presents an approach to the design of a learning environment in a mathematical domain (elementary combinatorics) where problem solving is based more on modelling than o...
Gérard Tisseau, Hélène Giroir...
AAAI
1997
13 years 8 months ago
Reinforcement Learning with Time
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
Daishi Harada
ICML
1996
IEEE
13 years 11 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
IJHIS
2006
94views more  IJHIS 2006»
13 years 7 months ago
A new fine-grained evolutionary algorithm based on cellular learning automata
In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary ...
Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri