World's Best Scientists 2026 revealed!
Fahiem Bacchus

Fahiem Bacchus

D-Index & Metrics

Computer Science

D-Index
55
Citations
11612
World Ranking
4333
National Ranking
173

Research.com Recognitions

  • 2006 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions in knowledge representation, automated planning, utility modeling, and algorithms for SAT and constraint satisfaction.

Overview

Fahiem Bacchus is affiliated with the University of Toronto in Canada. Their research spans across several fields within computer science and engineering, focusing primarily on artificial intelligence and related subfields.

The main fields of study for Bacchus include:

  • Computer Science
  • Engineering

Within these fields, their research is concentrated in the following subfields:

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Industrial and Manufacturing Engineering

The primary topics of Bacchus' scholarly work cover:

  • Constraint Satisfaction and Optimization
  • Formal Methods in Verification
  • AI-based Problem Solving and Planning
  • Logic, Reasoning, and Knowledge
  • Optimization and Packing Problems
  • Bayesian Modeling and Causal Inference
  • Machine Learning and Algorithms

Bacchus has contributed to several conferences and publication venues, including:

  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Recent published papers include:

  • MAXSAT Heuristics for Cost Optimal Planning, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Learning Branching Heuristics for Propositional Model Counting, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Large Neighbourhood Search for Anytime MaxSAT Solving, 2022, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Frequent collaborators in Bacchus' research projects are:

  • Randy Hickey
  • Lei Zhang
  • Matti Järvisalo
  • Ruben Martins
  • Jeremias Berg

Among Bacchus' recognitions is the distinction of Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), awarded in 2006 for significant contributions in knowledge representation, automated planning, utility modeling, and algorithms for SAT and constraint satisfaction.

Best Publications

  • LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE

    Wai Lam;Fahiem Bacchus

  • Using temporal logics to express search control knowledge for planning

    Fahiem Bacchus;Froduald Kabanza

  • Representing and reasoning with probabilistic knowledge

    Fahiem Ivor Bacchus

  • Planning for temporally extended goals

    Fahiem Bacchus;Froduald Kabanza

  • Extending the knowledge-based approach to planning with incomplete information and sensing

    Ronald P. A. Petrick;Fahiem Bacchus

  • Graphical models for preference and utility

    Fahiem Bacchus;Adam Grove

  • Representing and reasoning with probabilistic knowledge: a logical approach to probabilities

    Fahiem Bacchus

  • A knowledge-based approach to planning with incomplete information and sensing

    Ronald P. A. Petrick;Fahiem Bacchus

  • From statistical knowledge bases to degrees of belief

    Fahiem Bacchus;Adam J. Grove;Joseph Y. Halpern;Daphne Koller

  • Combining Component Caching and Clause Learning for Effective Model Counting.

    Tian Sang;Fahiem Bacchus;Paul Beame;Henry A. Kautz

  • UCP-Networks: A Directed Graphical Representation of Conditional Utilities

    Craig Boutilier;Fahiem Bacchus;Ronen I. Brafman

  • On the Conversion between Non-Binary and Binary Constraint Satisfaction Problems

    Fahiem Bacchus;Peter van Beek

  • AIPS 2000 Planning Competition: The Fifth International Conference on Artificial Intelligence Planning and Scheduling Systems

    Fahiem Bacchus

  • Reasoning about noisy sensors and effectors in the situation calculus

    Fahiem Bacchus;Joseph Y. Halpern;Hector J. Levesque

  • A heuristic search approach to planning with temporally extended preferences

    Jorge A. Baier;Fahiem Bacchus;Sheila A. McIlraith

  • Effective Preprocessing with Hyper-Resolution and Equality Reduction

    Fahiem Bacchus;Jonathan Winter

  • Downward refinement and the efficiency of hierarchical problem solving

    Fahiem Bacchus;Qiang Yang

  • Solving MAXSAT by solving a sequence of simpler SAT instances

    Jessica Davies;Fahiem Bacchus

  • Algorithms and complexity results for #SAT and Bayesian inference

    F. Bacchus;S. Dalmao;T. Pitassi

  • Maximum satisfiability using core-guided MAXSAT resolution

    Nina Narodytska;Fahiem Bacchus

Frequent Co-Authors

Joseph Y. Halpern
Joseph Y. Halpern Cornell University
Daphne Koller
Daphne Koller insitro Inc.
Toniann Pitassi
Toniann Pitassi Columbia University
Toby Walsh
Toby Walsh University of New South Wales
Wai Lam
Wai Lam Chinese University of Hong Kong
Craig Boutilier
Craig Boutilier Google (United States)
Hector J. Levesque
Hector J. Levesque University of Toronto
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Peter van Beek
Peter van Beek University of Waterloo
Allen Van Gelder
Allen Van Gelder University of California, Santa Cruz

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