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ECML
2004
Springer
15 years 11 months ago
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Pieter Jan't Hoen, Karl Tuyls
LSO
2004
Springer
15 years 11 months ago
COTS Evaluation Supported by Knowledge Bases
Selection of Commercial-off-The-Shelf (COTS) software products is a knowledge-intensive process. In this paper, we show how knowledge bases can be used to facilitate the COTS selec...
Abdallah Mohamed, Tom Wanyama, Günther Ruhe, ...
AMEC
2003
Springer
15 years 11 months ago
Choosing Samples to Compute Heuristic-Strategy Nash Equilibrium
Auctions define games of incomplete information for which it is often too hard to compute the exact Bayesian-Nash equilibrium. Instead, the infinite strategy space is often popu...
William E. Walsh, David C. Parkes, Rajarshi Das
CP
2003
Springer
15 years 11 months ago
Automated Mechanism Design: A New Application Area for Search Algorithms
Mechanism design is the art of designing the rules of the game (aka. mechanism) so that a desirable outcome (according to a given objective) is reached despite the fact that each a...
Tuomas Sandholm
ILP
2003
Springer
15 years 11 months ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon