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AIPS
1998
13 years 9 months ago
Solving Stochastic Planning Problems with Large State and Action Spaces
Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
Thomas Dean, Robert Givan, Kee-Eung Kim
EUROCAST
2007
Springer
132views Hardware» more  EUROCAST 2007»
14 years 10 days ago
Using Omnidirectional BTS and Different Evolutionary Approaches to Solve the RND Problem
RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor network...
Miguel A. Vega-Rodríguez, Juan Antonio G&oa...
GECCO
2003
Springer
14 years 1 months ago
A Kernighan-Lin Local Improvement Heuristic That Solves Some Hard Problems in Genetic Algorithms
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
William A. Greene
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
14 years 1 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
EUROSYS
2006
ACM
14 years 5 months ago
Solving the starting problem: device drivers as self-describing artifacts
Run-time conflicts can affect even the most rigorously tested software systems. A reliance on execution-based testing makes it prohibitively costly to test every possible interac...
Michael F. Spear, Tom Roeder, Orion Hodson, Galen ...