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NIPS
1992
13 years 8 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
MM
2009
ACM
252views Multimedia» more  MM 2009»
14 years 2 months ago
Localizing volumetric motion for action recognition in realistic videos
This paper presents a novel motion localization approach for recognizing actions and events in real videos. Examples include StandUp and Kiss in Hollywood movies. The challenge ca...
Xiao Wu, Chong-Wah Ngo, Jintao Li, Yongdong Zhang
AAAI
1997
13 years 8 months ago
Reinforcement Learning with Time
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
Daishi Harada
AAAI
2000
13 years 8 months ago
A Method for Clustering the Experiences of a Mobile Robot that Accords with Human Judgments
If robotic agents are to act autonomously they must have the ability to construct and reason about models of their physical environment. For example, planning to achieve goals req...
Tim Oates, Matthew D. Schmill, Paul R. Cohen
ICRA
1995
IEEE
79views Robotics» more  ICRA 1995»
13 years 11 months ago
Learning to predict Resistive Forces During Robotic Excavation
— Few robot tasks require as forceful an interaction with the world as excavation. In order to effectively plan its actions, our robot excavator requires a method that allows it ...
Sanjiv Singh