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ICML
2004
IEEE
14 years 8 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
JMLR
2011
133views more  JMLR 2011»
13 years 2 months ago
Operator Norm Convergence of Spectral Clustering on Level Sets
Following Hartigan (1975), a cluster is defined as a connected component of the t-level set of the underlying density, that is, the set of points for which the density is greater...
Bruno Pelletier, Pierre Pudlo
GECCO
2010
Springer
148views Optimization» more  GECCO 2010»
14 years 5 days ago
Guarding against premature convergence while accelerating evolutionary search
The fundamental dichotomy in evolutionary algorithms is that between exploration and exploitation. Recently, several algorithms [8, 9, 14, 16, 17, 20] have been introduced that gu...
Josh C. Bongard, Gregory S. Hornby
EC
2002
180views ECommerce» more  EC 2002»
13 years 7 months ago
Combining Convergence and Diversity in Evolutionary Multiobjective Optimization
Over the past few years, the research on evolutionary algorithms has demonstrated their niche in solving multiobjective optimization problems, where the goal is to nd a number of ...
Marco Laumanns, Lothar Thiele, Kalyanmoy Deb, Ecka...
ATAL
2007
Springer
14 years 1 months ago
Regret based dynamics: convergence in weakly acyclic games
Regret based algorithms have been proposed to control a wide variety of multi-agent systems. The appeal of regretbased algorithms is that (1) these algorithms are easily implement...
Jason R. Marden, Gürdal Arslan, Jeff S. Shamm...