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AGENTS
1998
Springer
15 years 10 months ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso
ECTEL
2006
Springer
15 years 10 months ago
Getting to Know Your Student in Distance Learning Contexts
Abstract. Good teachers know their students, and exploit this knowledge to adapt or optimise their instruction. Teachers know their students because they interact with them face-to...
Claus Zinn, Oliver Scheuer
AAMAS
2006
Springer
15 years 6 months ago
An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 6 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
ICRA
2006
IEEE
87views Robotics» more  ICRA 2006»
16 years 16 days ago
Learning to Predict Slip for Ground Robots
— In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do t...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...