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HRI
2007
ACM
13 years 11 months ago
Learning by demonstration with critique from a human teacher
Learning by demonstration can be a powerful and natural tool for developing robot control policies. That is, instead of tedious hand-coding, a robot may learn a control policy by ...
Brenna Argall, Brett Browning, Manuela M. Veloso
ICRA
2009
IEEE
259views Robotics» more  ICRA 2009»
14 years 2 months ago
Constructing action set from basis functions for reinforcement learning of robot control
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
Akihiko Yamaguchi, Jun Takamatsu, Tsukasa Ogasawar...
CORR
2008
Springer
189views Education» more  CORR 2008»
13 years 7 months ago
Algorithms for Dynamic Spectrum Access with Learning for Cognitive Radio
We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperati...
Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli
ASSETS
2005
ACM
13 years 9 months ago
Automating tactile graphics translation
Access to graphical images (bar charts, diagrams, line graphs, etc.) that are in a tactile form (representation through which content can be accessed by touch) is inadequate for s...
Richard E. Ladner, Melody Y. Ivory, Rajesh Rao, Sh...
IEEEPACT
2008
IEEE
14 years 1 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...