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ANTSW
2010
Springer
13 years 5 months ago
Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem
Ant colony optimization (ACO) has been widely used for different combinatorial optimization problems. In this paper, we investigate ACO algorithms with respect to their runtime beh...
Timo Kötzing, Frank Neumann, Heiko Rögli...
ECML
2007
Springer
13 years 11 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
GECCO
2007
Springer
193views Optimization» more  GECCO 2007»
14 years 1 months ago
Approximating covering problems by randomized search heuristics using multi-objective models
The main aim of randomized search heuristics is to produce good approximations of optimal solutions within a small amount of time. In contrast to numerous experimental results, th...
Tobias Friedrich, Nils Hebbinghaus, Frank Neumann,...
AAAI
2007
13 years 9 months ago
UNDERTOW: Multi-Level Segmentation of Real-Valued Time Series
The discovery of meaningful change points, finding segments, in both categorical and real-value data time series is a well-studied problem. Prior segmentation algorithms and task...
Tom Armstrong, Tim Oates
GECCO
2008
Springer
156views Optimization» more  GECCO 2008»
13 years 8 months ago
Computing minimum cuts by randomized search heuristics
We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimiz...
Frank Neumann, Joachim Reichel, Martin Skutella