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» Learning Partially Observable Deterministic Action Models
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JAIR
2002
120views more  JAIR 2002»
13 years 7 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
AIPS
2008
13 years 10 months ago
Multiagent Planning Under Uncertainty with Stochastic Communication Delays
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos A. ...
JIRS
2000
144views more  JIRS 2000»
13 years 7 months ago
An Integrated Approach of Learning, Planning, and Execution
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
Ramón García-Martínez, Daniel...
AAAI
2000
13 years 9 months ago
Back to the Future for Consistency-Based Trajectory Tracking
Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the p...
James Kurien, P. Pandurang Nayak
ACML
2009
Springer
14 years 2 months ago
Injecting Structured Data to Generative Topic Model in Enterprise Settings
Enterprises have accumulated both structured and unstructured data steadily as computing resources improve. However, previous research on enterprise data mining often treats these ...
Han Xiao, Xiaojie Wang, Chao Du