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» Solving iterated functions using genetic programming
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111
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AIPS
2008
15 years 5 months ago
Learning Heuristic Functions through Approximate Linear Programming
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
Marek Petrik, Shlomo Zilberstein
SEKE
2007
Springer
15 years 9 months ago
Incremental Effort Prediction Models in Agile Development using Radial Basis Functions
One of the impediments to the wide dissemination of software estimation and measurement practices is the significant overhead imposed by these practices on the project and develop...
Raimund Moser, Witold Pedrycz, Giancarlo Succi
131
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ECML
2006
Springer
15 years 7 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
121
Voted
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 7 months ago
Identification of weak motifs in multiple biological sequences using genetic algorithm
Recognition of motifs in multiple unaligned sequences provides an insight into protein structure and function. The task of discovering these motifs is very challenging because mos...
Topon Kumar Paul, Hitoshi Iba
115
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EUSFLAT
2007
134views Fuzzy Logic» more  EUSFLAT 2007»
15 years 5 months ago
Selection of Optimal Set of Diagnostic Tests with Use of Evolutionary Approach in Intelligent Systems
This paper concerns problem of selection of optimal subset of irredundant unconditional diagnostic tests by means of evolutionary approach. The method of correction of features’...
A. E. Yankovskaya, Y. R. Tsoy