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» The State Problem for Evolutionary Testing
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ALT
2005
Springer
15 years 7 months ago
Learnability of Probabilistic Automata via Oracles
Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed µ-distinguishable. In this paper, we prove that state merging alg...
Omri Guttman, S. V. N. Vishwanathan, Robert C. Wil...
ATAL
2005
Springer
15 years 3 months ago
Using decision-theoretic models to enhance agent system survivability
A survivable agent system depends on the incorporation of many recovery features. However, the optimal use of these features requires the ability to assess the actual state of the...
Anthony R. Cassandra, Marian H. Nodine, Shilpa Bon...
ICGA
1997
133views Optimization» more  ICGA 1997»
14 years 11 months ago
Messy Genetic Algorithms for Subset Feature Selection
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...
TSMC
2008
147views more  TSMC 2008»
14 years 10 months ago
A New Approach for Solving Nonlinear Equations Systems
This paper proposes a new perspective for solving systems of complex nonlinear equations by simply viewing them as a multiobjective optimization problem. Every equation in the syst...
Crina Grosan, Ajith Abraham
ICANN
2005
Springer
15 years 3 months ago
Evolution of Heuristics for Give-Away Checkers
The efficacy of two evolutionary approaches to the problem of generation of heuristical linear and non-linear evaluation functions in the game of give-away checkers is tested in th...
Magdalena Kusiak, Karol Waledzik, Jacek Mandziuk