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GECCO
2009
Springer
110views Optimization» more  GECCO 2009»
15 years 11 months ago
EMO shines a light on the holes of complexity space
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
Núria Macià, Albert Orriols-Puig, Es...
ICML
1996
IEEE
15 years 11 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
ATAL
2008
Springer
15 years 8 months ago
MB-AIM-FSI: a model based framework for exploiting gradient ascent multiagent learners in strategic interactions
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Doran Chakraborty, Sandip Sen
ATMOS
2007
119views Optimization» more  ATMOS 2007»
15 years 8 months ago
Models for Railway Track Allocation
The optimal track allocation problem (OPTRA) is to find, in a given railway network, a conflict free set of train routes of maximum value. We study two types of integer programmi...
Ralf Borndörfer, Thomas Schlechte
GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
15 years 7 months ago
Speed-up techniques for solving large-scale bTSP with the Two-Phase Pareto Local Search
We first present a method, called Two-Phase Pareto Local Search, to find a good approximation of the efficient set of the biobjective traveling salesman problem. In the first p...
Thibaut Lust