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» Observation Can Be as Effective as Action in Problem Solving
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IROS
2009
IEEE
206views Robotics» more  IROS 2009»
14 years 3 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...
IROS
2008
IEEE
118views Robotics» more  IROS 2008»
14 years 3 months ago
Laban Movement Analysis for multi-ocular systems
Abstract— We present as a contribution to the field of humanmachine interaction a system that analyzes human movements online through multiple observers, based on the concept of...
Jörg Rett, Luis Santos, Jorge Dias
VLDB
2004
ACM
104views Database» more  VLDB 2004»
14 years 9 months ago
Retrieval effectiveness of an ontology-based model for information selection
Technology in the field of digital media generates huge amounts of nontextual information, audio, video, and images, along with more familiar textual information. The potential for...
Latifur Khan, Dennis McLeod, Eduard H. Hovy
AAMAS
2000
Springer
13 years 8 months ago
Algorithms for Distributed Constraint Satisfaction: A Review
When multiple agents are in a shared environment, there usually exist constraints among the possible actions of these agents. A distributed constraint satisfaction problem (distrib...
Makoto Yokoo, Katsutoshi Hirayama
NIPS
2004
13 years 10 months ago
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
Pascal Poupart, Craig Boutilier