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AAAI
1997
15 years 2 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan
114
Voted
AMC
2004
115views more  AMC 2004»
15 years 15 days ago
Performance comparison of memetic algorithms
Local search techniques have been applied in optimization methods. The effect of local search to the memetic algorithms can make multimodal and non-linear problems easier to solve...
Jason G. Digalakis, Konstantinos G. Margaritis
101
Voted
ICDCN
2010
Springer
15 years 7 months ago
A Leader-Free Byzantine Consensus Algorithm
The paper considers the consensus problem in a partially synchronous system with Byzantine faults. It turns out that, in the partially synchronous system, all deterministic algorit...
Fatemeh Borran, André Schiper
104
Voted
IPPS
2003
IEEE
15 years 6 months ago
A Genetic Approach to Planning in Heterogeneous Computing Environments
Planning is an artificial intelligence problem with a wide range of real-world applications. Genetic algorithms, neural networks, and simulated annealing are heuristic search met...
Han Yu, Dan C. Marinescu, Annie S. Wu, Howard Jay ...
99
Voted
PPL
2006
93views more  PPL 2006»
15 years 17 days ago
Inherently Parallel Geometric Computations
A new computational paradigm is described which o ers the possibility of superlinear and sometimes unbounded speedup, when parallel computation is used. The computations involved ...
Selim G. Akl