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ATAL
2007
Springer
15 years 10 months ago
Confidence-based policy learning from demonstration using Gaussian mixture models
We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
Sonia Chernova, Manuela M. Veloso
AIPS
1998
15 years 8 months ago
Solving Stochastic Planning Problems with Large State and Action Spaces
Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
Thomas Dean, Robert Givan, Kee-Eung Kim
CVPR
2008
IEEE
16 years 8 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
KCAP
2005
ACM
16 years 10 days ago
An ontological approach to the construction of problem-solving models
Our ongoing work aims at defining an ontology-centered approach for building expertise models for the CommonKADS methodology. This approach (which is named "OntoKADS") i...
Sabine Bruaux, Gilles Kassel, Gilles Morel
PADS
2005
ACM
16 years 10 days ago
Simulating Realistic Packet Routing without Routing Protocols
A fundamental requirement for any network simulation environment is the realistic forwarding of packets from a source to a destination in the simulated topology. The routing decis...
George F. Riley, Dheeraj Reddy