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TSMC
2008
229views more  TSMC 2008»
13 years 8 months ago
A Comprehensive Survey of Multiagent Reinforcement Learning
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
Lucian Busoniu, Robert Babuska, Bart De Schutter
RECSYS
2009
ACM
14 years 3 months ago
Measuring predictive capability in collaborative filtering
This paper presents a new memory-based approach to Collaborative Filtering where the neighbors of the active user will be selected taking into account their predictive capability....
Luis M. de Campos, Juan M. Fernández-Luna, ...
GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
14 years 3 months ago
Meta-optimizing semantic evolutionary search
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution. Distributions are not esti...
Moshe Looks
CHI
2011
ACM
13 years 14 days ago
Breath control of amusement rides
Emerging robotic technologies are enabling the control of individual seats on rollercoasters and other thrill rides. We explore the potential of breathing as an effective and enga...
Joe Marshall, Duncan Rowland, Stefan Rennick Eggle...
SIGCSE
2004
ACM
125views Education» more  SIGCSE 2004»
14 years 2 months ago
Agent-based cooperative learning: a proof-of-concept experiment
This paper presents an innovative multiagent system to support cooperative learning among students both in the real classrooms and in distance education. The system, called I-MIND...
Leen-Kiat Soh, Hong Jiang, Charles Ansorge