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FUIN
2008
108views more  FUIN 2008»
15 years 5 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
16 years 1 months ago
Learning Complementary Multiagent Behaviors: A Case Study
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
Shivaram Kalyanakrishnan, Peter Stone
ICML
2003
IEEE
16 years 7 months ago
AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Oppon
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
Vincent Conitzer, Tuomas Sandholm
ESANN
2008
15 years 8 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
ECTEL
2009
Springer
15 years 10 months ago
Remote Hands-On Experience: Distributed Collaboration with Augmented Reality
One claim of Technology-Enhanced Learning (TEL) is to support and exploit benefits from distance learning and remote collaboration. On the other hand, several approaches to learnin...
Matthias Krauß, Kai Riege, Marcus Winter, Ly...