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HAPTICS
2007
IEEE
16 years 1 months ago
Haptic Feedback Enhances Force Skill Learning
This paper explores the use of haptic feedback to abstract motor skill that requires recalling a sequence of forces. Participants are guided along a trajectory and are asked to le...
Daniel Morris, Hong Z. Tan, Federico Barbagli, Tim...
IAT
2010
IEEE
15 years 5 months ago
A Biologically-Inspired Cognitive Agent Model Integrating Declarative Knowledge and Reinforcement Learning
Abstract--The paper proposes a biologically-inspired cognitive agent model, known as FALCON-X, based on an integration of the Adaptive Control of Thought (ACT-R) architecture and a...
Ah-Hwee Tan, Gee Wah Ng
ACL
2012
13 years 9 months ago
Learning High-Level Planning from Text
Comprehending action preconditions and effects is an essential step in modeling the dynamics of the world. In this paper, we express the semantics of precondition relations extrac...
S. R. K. Branavan, Nate Kushman, Tao Lei, Regina B...
ICCV
2007
IEEE
16 years 9 months ago
Boosting Invariance and Efficiency in Supervised Learning
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
Andrea Vedaldi, Paolo Favaro, Enrico Grisan
EVOW
2010
Springer
16 years 1 months ago
Learning to Dance through Interactive Evolution
A relatively rare application of artificial intelligence at the nexus of art and music is dance. The impulse shared by all humans to express ourselves through dance represents a u...
Greg A. Dubbin, Kenneth O. Stanley