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Guided Incremental Construction of Belief Networks (2003) [2 citations — 1 self]

by Charles Sutton ,  Brendan Burns ,  Clayton Morrison ,  Paul R. Cohen
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Abstract:

Because uncertain reasoning is often intractable, it is hard to reason with a large amount of knowledge.

Citations

4701 Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference – Pearl - 1988
2210 Artificial Intelligence: A Modern Approach – Russell, Norvig - 1995
601 A tutorial on learning with Bayesian networks – Heckerman - 1998
256 The HEARSAY-II speech-understanding system: Integrating knowledge to resolve uncertainty”. Computing Surveys 12(2 – Erman, Hayes-Roth, et al.
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122 Object-Oriented Bayesian Networks – Koller, Pfeffer - 1997
60 Network fragments: Representing knowledge for constructing probabilistic models – Laskey, Mahoney - 1997
60 Blackboard Systems – Nii
57 The evolution of blackboard control architectures – Carver, Lesser - 1994
53 Computation and action under bounded resources – Horvitz - 1990
52 A generalization of the noisy-or model – Srinivas - 1993
42 A language for construction of belief networks – Goldman, Charniak - 1993
41 A New Framework for sensor Interpretation: Planning to Resolve Sources of Uncertainty – Carver
40 SPOOK: A system for probabilistic objectoriented knowledge representation. Paper presented at the Uncertainty – Pfeffer, Koller, et al. - 1999
31 A Planner for the Control of Problem Solving Systems – Carver, Lesser - 1993
8 SPT: Hierarchical Agent Control: A framework for defining agent behavior – Atkin, King, et al. - 2001
4 Domain-general simulation and planning with physical schemas – Atkin, Westbrook, et al. - 2000
2 Temporal abstraction in Bayesian networks – Burns, Morrison - 2003
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