• Publications
  • Influence
Using temporal logics to express search control knowledge for planning
TLDR
This work shows how domain dependent search control knowledge can be represented in a temporal logic, and then utilized to effectively control a forward-chaining planner. Expand
LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE
TLDR
A new approach for learning Bayesian belief networks from raw data is presented, based on Rissanen's minimal description length (MDL) principle, which can learn unrestricted multiply‐connected belief networks and allows for trade off accuracy and complexity in the learned model. Expand
Solving MAXSAT by Solving a Sequence of Simpler SAT Instances
TLDR
This paper introduces a new MAXSAT algorithm that solves a sequence of SAT instances and can, however, require solving more SAT instances than previous approaches, which is simpler than previous methods and displays superior performance on some benchmarks. Expand
A Knowledge-Based Approach to Planning with Incomplete Information and Sensing
TLDR
This paper has constructed a planner to utilize a higher level, "knowledge-based", representation of the planner's knowledge and of the domain actions and shows that on many common problems this more abstract representation is perfectly adequate for solving the planning problem, and that in fact it scales better and supports features that make it applicable to much richer domains and problems. Expand
Combining Component Caching and Clause Learning for Effective Model Counting
TLDR
A model-counting program that combines component caching with clause learning, one of the most important ideas used in modern SAT solvers, and provides significant evidence that it can outperform existing algorithms for #SAT by orders of magnitude. Expand
Graphical models for preference and utility
TLDR
This work surveys existing notions of independence for utility functions in a multi-attribute space, and suggests that these can be used to achieve similar advantages in order to speed up expected utility calculations. Expand
Exploiting the Power of mip Solvers in maxsat
TLDR
An extensive empirical evaluation of a number of maxsat solvers is presented and a previously developed hybrid approach for solving maxsat is extended, that utilizes both a sat solver and a mip solver, which is shown to be quite effective. Expand
Representing and reasoning with probabilistic knowledge - a logical approach to probabilities
  • F. Bacchus
  • Mathematics, Computer Science
  • 3 January 1991
TLDR
This book explores logical formalisms for representing and reasoning with probabilistic information that will be of particular value to researchers in nonmonotonic reasoning, applications of probabilities, and knowledge representation. Expand
Planning for temporally extended goals
  • F. Bacchus, F. Kabanza
  • Computer Science
  • Annals of Mathematics and Artificial Intelligence
  • 4 August 1996
TLDR
A logical language, a temporal logic, for specifying goals with desirable sequences of states, and a plan to be correct if its execution yields one of these desirable sequences. Expand
From Statistical Knowledge Bases to Degrees of Belief
TLDR
This paper describes one approach for inducing degrees of belief from very rich knowledge bases, that can include information about particular individuals, statistical correlations, physical laws, and default rules, and shows that a number of desiderata that arise in direct inference and default reasoning follow directly from the semantics of random worlds. Expand
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