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JAIR
2002
120views more  JAIR 2002»
15 years 6 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
IPSN
2010
Springer
15 years 3 months ago
i-MAC - a MAC that learns
Traffic patterns in manufacturing machines exhibit strong temporal correlations due to the underlying repetitive nature of their operations. A MAC protocol can potentially learn t...
Krishna Kant Chintalapudi
EPIA
2005
Springer
16 years 4 days ago
Learning to Select Negotiation Strategies in Multi-agent Meeting Scheduling
In this paper, we look at the Multi-Agent Meeting Scheduling problem where distributed agents negotiate meeting times on behalf of their users. While many negotiation approaches ha...
Elisabeth Crawford, Manuela M. Veloso
IFIP
1997
Springer
15 years 10 months ago
Representing a body of knowledge for teaching, learning and assessment
: National and international standards for professional groups may become a dominant and governing force as internet-based professional training becomes universally accepted. Educa...
Don Sheridan, David White
147
Voted
ICRA
1995
IEEE
79views Robotics» more  ICRA 1995»
15 years 10 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