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HIS
2004
14 years 11 months ago
Reinforcement Learning Hierarchical Neuro-Fuzzy Politree Model for Control of Autonomous Agents
: This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence...
Karla Figueiredo, Marley B. R. Vellasco, Marco Aur...
EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
15 years 3 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
CHI
2009
ACM
15 years 10 months ago
Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool
We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...
IJCNN
2006
IEEE
15 years 3 months ago
Reinforcement Learning for Parameterized Motor Primitives
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
Jan Peters, Stefan Schaal
HICSS
2005
IEEE
166views Biometrics» more  HICSS 2005»
15 years 3 months ago
Prototyping the Emergence of Collaborative Knowledge
E-learning growth is driven by global, societal, and technological changes that both enable and require increased worker and learner mobility, access to distributed domain experti...
Rita M. Vick, Apperson H. Johnson