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NIPS
2000
15 years 5 months ago
Balancing Multiple Sources of Reward in Reinforcement Learning
For many problems which would be natural for reinforcement learning, the reward signal is not a single scalar value but has multiple scalar components. Examples of such problems i...
Christian R. Shelton
127
Voted
ICRA
2007
IEEE
157views Robotics» more  ICRA 2007»
15 years 10 months ago
Learning to Select State Machines using Expert Advice on an Autonomous Robot
— Hierarchical state machines have proven to be a powerful tool for controlling autonomous robots due to their flexibility and modularity. For most real robot implementations, h...
Brenna Argall, Brett Browning, Manuela M. Veloso
139
Voted
HICSS
2003
IEEE
95views Biometrics» more  HICSS 2003»
15 years 9 months ago
Matching Needs - Application Service Providing for Asynchronous Learning Networks
Universities have severe difficulties in using elearning applications successfully due to organizational problems to provide them. Providing a web-based learning environment is an...
Wolf-Gideon Bleek, Iver Jackewitz, Bernd Pape
132
Voted
NIPS
1994
15 years 5 months ago
Interference in Learning Internal Models of Inverse Dynamics in Humans
Experiments were performed to reveal some of the computational properties of the human motor memory system. We show that as humans practice reaching movements while interacting wi...
Reza Shadmehr, Tom Brashers-Krug, Ferdinando A. Mu...
124
Voted
AROBOTS
2000
137views more  AROBOTS 2000»
15 years 3 months ago
Acquiring Mobile Robot Behaviors by Learning Trajectory Velocities
Abstract. The development of robots that learn from experience is a relentless challenge confronting artificial intelligence today. This paper describes a robot learning method whi...
Koren Ward, Alexander Zelinsky