World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
11388
World Ranking
5567
National Ranking
88

Research.com Recognitions

  • 2017 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to algorithms, representation, and theoretical foundations of automated decision making in the areas of preference handling, planning under uncertainty, multi-agent planning, and privacy.

Overview

Ronen I. Brafman is affiliated with Ben-Gurion University of the Negev in Israel. Their research predominantly lies within the broad field of Computer Science, with a focus on Artificial Intelligence.

The main areas of study in their work include:

  • AI-based Problem Solving and Planning
  • Machine Learning and Algorithms
  • Logic, Reasoning, and Knowledge
  • Formal Methods in Verification
  • Robotic Path Planning Algorithms
  • Reinforcement Learning in Robotics
  • Bayesian Modeling and Causal Inference

Frequent co-authors who have collaborated with them include:

  • Guy Shani
  • Or Wertheim
  • Shashank Shekhar
  • Dan R. Suissa
  • Elias Goldsztejn

Ronen I. Brafman has published extensively in several venues, with the most frequent being:

  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the International Conference on Automated Planning and Scheduling
  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • Electronic Proceedings in Theoretical Computer Science

Some of Ronen I. Brafman's recent papers are:

  • A Multi-Path Compilation Approach to Contingent Planning, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Probabilistic Programs as an Action Description Language, 2023, Proceedings of the AAAI Conference on Artificial Intelligence

Other relevant publications from related authors, often co-authored or in similar venues, include:

  • Lifted MEU by Weighted Model Counting, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Reinforcement Learning with Non-Markovian Rewards, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • A Factored Approach to Deterministic Contingent Multi-Agent Planning, 2021, Proceedings of the International Conference on Automated Planning and Scheduling

In recognition of their contributions, Ronen I. Brafman was named a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2017. The award citation highlights work in algorithms, representation, and theoretical foundations of automated decision making, particularly in preference handling, planning under uncertainty, multi-agent planning, and privacy.

Best Publications

  • R-max - a general polynomial time algorithm for near-optimal reinforcement learning

    Ronen I. Brafman;Moshe Tennenholtz

  • CP-nets: a tool for representing and reasoning with conditional ceteris paribus preference statements

    Craig Boutilier;Ronen I. Brafman;Carmel Domshlak;Holger H. Hoos

  • An MDP-Based Recommender System

    Guy Shani;David Heckerman;Ronen I. Brafman

  • Reasoning with conditional ceteris paribus preference statements

    Craig Boutilier;Ronen I. Brafman;Holger H. Hoos;David Poole

  • CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements

    C. Boutilier;R. I. Brafman;C. Domshlak;H. H. Hoos

  • From one to many: planning for loosely coupled multi-agent systems

    Ronen I. Brafman;Carmel Domshlak

  • Conformant planning via heuristic forward search: a new approach

    Jörg Hoffmann;Ronen I. Brafman

  • Contingent planning via heuristic forward search with implicit belief states

    Jörg Hoffmann;Ronen I. Brafman

  • Preference-Based Constrained Optimization with CP-Nets

    Craig Boutilier;Ronen I. Brafman;Carmel Domshlak;Holger H. Hoos

  • Conformant planning via heuristic forward search: a new approach

    Ronen I. Brafman;Jörg Hoffmann

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

    Craig Boutilier;Fahiem Bacchus;Ronen I. Brafman

  • Contingent Planning via Heuristic Forward Search with Implicit Belief States

    Jörg Hoffmann;Ronen Brafman;Susanne Biundo;Karen Meyers

  • On graphical modeling of preference and importance

    Ronen I. Brafman;Carmel Domshlak;Solomon E. Shimony

  • Designing with interactive example galleries

    Brian Lee;Savil Srivastava;Ranjitha Kumar;Ronen Brafman

  • A simplifier for propositional formulas with many binary clauses

    R.I. Brafman

  • Partial-order planning with concurrent interacting actions

    Craig Boutilier;Ronen I. Brafman

  • An MDP-based recommender system

    Guy Shani;Ronen I. Brafman;David Heckerman

  • Introducing variable importance tradeoffs into CP-nets

    Ronen I. Brafman;Carmel Domshlak

  • Preference Handling - An Introductory Tutorial

    Ronen I. Brafman;Carmel Domshlak

  • A heuristic variable grid solution method for POMDPs

    Ronen I. Brafman

  • CP-nets: a tool for represent-ing and reasoning with conditional ceteris paribus state-ments

    Craig Boutilier;Ronen I. Brafman;Carmel Domshlak;Holger H. Hoos

Frequent Co-Authors

Carmel Domshlak
Carmel Domshlak Technion – Israel Institute of Technology
Moshe Tennenholtz
Moshe Tennenholtz Technion – Israel Institute of Technology
Craig Boutilier
Craig Boutilier Google (United States)
Yoav Shoham
Yoav Shoham Stanford University
Giuseppe De Giacomo
Giuseppe De Giacomo Sapienza University of Rome
Holger H. Hoos
Holger H. Hoos RWTH Aachen University
David Poole
David Poole University of British Columbia
Jörg Hoffmann
Jörg Hoffmann Saarland University
David Heckerman
David Heckerman Microsoft (United States)
Jean-Claude Latombe
Jean-Claude Latombe Stanford University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees in Computer Science opens up a variety of career pathways that offer flexibility and strong earning potential. Many students are interested in quick degrees that pay well, allowing them to enter the workforce faster and start building their careers with competitive salaries. These accelerated programs can be a smart option for those looking to transition careers or upskill quickly.

For those interested in specialized fields, pursuing the best online masters in artificial intelligence can open doors to emerging tech sectors and high-demand roles in AI and machine learning. Meanwhile, it's helpful to consider your academic strengths and long-term goals when choosing a program in college—as some majors align better with the fast-evolving job market in technology.

If work-life balance and less-intensive coursework are important to you, you might also want to look into the easiest masters degree options available online. These programs can provide valuable credentials without undue stress, making advanced education more accessible for working professionals.

Best Scientists Citing Ronen I. Brafman

Trending Scientists

Recently Published Articles