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ICAART
2010
INSTICC
16 years 3 months ago
Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
Christos Dimitrakakis
GECCO
2008
Springer
116views Optimization» more  GECCO 2008»
15 years 7 months ago
A novel methodology for diversity preservation in evolutionary algorithms
In this paper we describe an improvement of an entropy-based diversity preservation approach for evolutionary algorithms. This approach exploits the information contained not only...
Giovanni Squillero, Alberto Paolo Tonda
GECCO
2004
Springer
124views Optimization» more  GECCO 2004»
15 years 12 months ago
Clustering with Niching Genetic K-means Algorithm
GA-based clustering algorithms often employ either simple GA, steady state GA or their variants and fail to consistently and efficiently identify high quality solutions (best known...
Weiguo Sheng, Allan Tucker, Xiaohui Liu
TSP
2008
116views more  TSP 2008»
15 years 6 months ago
Optimal Linear Precoding Strategies for Wideband Noncooperative Systems Based on Game Theory - Part I: Nash Equilibria
In this two-part paper, we propose a decentralized strategy, based on a game-theoretic formulation, to find out the optimal precoding/multiplexing matrices for a multipoint-to-mult...
Gesualdo Scutari, Daniel Pérez Palomar, Ser...
SODA
2004
ACM
115views Algorithms» more  SODA 2004»
15 years 8 months ago
Minimizing the stabbing number of matchings, trees, and triangulations
The (axis-parallel) stabbing number of a given set of line segments is the maximum number of segments that can be intersected by any one (axis-parallel) line. We investigate probl...
Sándor P. Fekete, Marco E. Lübbecke, H...