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CI
2005
106views more  CI 2005»
15 years 4 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird
UMUAI
1998
157views more  UMUAI 1998»
15 years 4 months ago
Bayesian Models for Keyhole Plan Recognition in an Adventure Game
We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users’ plans and...
David W. Albrecht, Ingrid Zukerman, Ann E. Nichols...
AMAI
2004
Springer
15 years 9 months ago
A Framework for Sequential Planning in Multi-Agent Settings
This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
Piotr J. Gmytrasiewicz, Prashant Doshi

Presentation
609views
17 years 3 months ago
Bus transit service planning and operations in a competitive environment
Transit services are currently facing several challenges in the United States and around the world. For many reasons, among which the fluctuations in gas prices and the state of t...
A. M. El-Geneidy, J. Hourdos, J. Horning
SSD
2005
Springer
108views Database» more  SSD 2005»
15 years 9 months ago
On Trip Planning Queries in Spatial Databases
In this paper we discuss a new type of query in Spatial Databases, called the Trip Planning Query (TPQ). Given a set of points of interest P in space, where each point belongs to ...
Feifei Li, Dihan Cheng, Marios Hadjieleftheriou, G...