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» Learning Generalized Plans Using Abstract Counting
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AGI
2008
13 years 10 months ago
Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
Brian Milch
ICML
2006
IEEE
14 years 9 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
AAAI
2012
11 years 10 months ago
Real-Time Collaborative Planning with the Crowd
Planning is vital to a wide range of domains, including robotics, military strategy, logistics, itinerary generation and more, that both humans and computers find difficult. Col...
Walter S. Lasecki, Jeffrey P. Bigham, James F. All...
CI
2005
106views more  CI 2005»
13 years 8 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
ICAC
2006
IEEE
14 years 2 months ago
Learning Application Models for Utility Resource Planning
Abstract— Shared computing utilities allocate compute, network, and storage resources to competing applications on demand. An awareness of the demands and behaviors of the hosted...
Piyush Shivam, Shivnath Babu, Jeffrey S. Chase