H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 84 Citations 37,476 258 World Ranking 344 National Ranking 213

Research.com Recognitions

Awards & Achievements

2019 - Member of the National Academy of Engineering For methods of reasoning about knowledge, belief, and uncertainty and their applications to distributed computing and multiagent systems.

2015 - Fellow of the American Academy of Arts and Sciences

2008 - ACM AAAI Allen Newell Award For fundamental advances in reasoning about knowledge, belief, and uncertainty and their groundbreaking applications in artificial intelligence, computer science, game theory, economics, and the philosophy of science.

2005 - Fellow of the American Association for the Advancement of Science (AAAS)

2002 - ACM Fellow For contributions to the modeling of and reasoning about uncertainty.

1993 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For sustained excellence in theoretical research on the logics of and relationships among knowledge, common knowledge, belief and probability.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Statistics

His scientific interests lie mostly in Artificial intelligence, Theoretical computer science, Mathematical economics, Knowledge representation and reasoning and Distributed computing. His Artificial intelligence study combines topics from a wide range of disciplines, such as Modal logic, Axiom, Semantics and Property. His work deals with themes such as Correctness, Computation, Secret sharing and Operator, which intersect with Theoretical computer science.

His Mathematical economics research is multidisciplinary, incorporating perspectives in Counterfactual conditional, Bayesian network, Relation and Rationality. He combines subjects such as Common knowledge, Procedural knowledge and Reasoning system with his study of Knowledge representation and reasoning. Joseph Y. Halpern works mostly in the field of Common knowledge, limiting it down to topics relating to Distributed knowledge and, in certain cases, Data science.

His most cited work include:

  • Reasoning About Knowledge (3413 citations)
  • Reasoning about Uncertainty (917 citations)
  • “Sometimes” and “not never” revisited: on branching versus linear time temporal logic (909 citations)

What are the main themes of his work throughout his whole career to date?

Joseph Y. Halpern mainly focuses on Mathematical economics, Theoretical computer science, Artificial intelligence, Discrete mathematics and Epistemology. Mathematical economics connects with themes related to Axiom in his study. His research investigates the connection between Theoretical computer science and topics such as Semantics that intersect with problems in Semantics.

His study in Non-monotonic logic and Knowledge representation and reasoning are all subfields of Artificial intelligence. His Discrete mathematics study frequently links to related topics such as Calculus. Particularly relevant to Best response is his body of work in Nash equilibrium.

He most often published in these fields:

  • Mathematical economics (24.32%)
  • Theoretical computer science (17.27%)
  • Artificial intelligence (16.12%)

What were the highlights of his more recent work (between 2014-2021)?

  • Mathematical economics (24.32%)
  • Causal model (3.74%)
  • Nash equilibrium (7.34%)

In recent papers he was focusing on the following fields of study:

Joseph Y. Halpern mainly investigates Mathematical economics, Causal model, Nash equilibrium, Probabilistic logic and Solution concept. His studies deal with areas such as Characterization, Bounded rationality and Rationality as well as Mathematical economics. His studies in Causal model integrate themes in fields like Epistemology, Causality, Outcome and Data science.

Joseph Y. Halpern has included themes like Value, Bayesian probability and Combinatorics in his Nash equilibrium study. His work carried out in the field of Probabilistic logic brings together such families of science as Simple, Theoretical computer science, Blockchain and Protocol. The True quantified Boolean formula research Joseph Y. Halpern does as part of his general Theoretical computer science study is frequently linked to other disciplines of science, such as Information acquisition, therefore creating a link between diverse domains of science.

Between 2014 and 2021, his most popular works were:

  • Actual Causality (101 citations)
  • Handbook of epistemic logic (42 citations)
  • Algorithmic rationality: Game theory with costly computation (41 citations)

In his most recent research, the most cited papers focused on:

  • Programming language
  • Artificial intelligence
  • Statistics

His primary scientific interests are in Mathematical economics, Causal model, Causality, Epistemology and Game theory. His work on Sequential equilibrium and Nash equilibrium is typically connected to Causality and Natural as part of general Mathematical economics study, connecting several disciplines of science. The study incorporates disciplines such as Abstraction, Basis, Theoretical computer science, Probabilistic logic and Outcome in addition to Causal model.

His Theoretical computer science research incorporates themes from Transformation, Modal logic, Unary operation and Distribution. His Epistemology research includes themes of Autonomous agent and Epistemic modal logic. His Game theory study combines topics in areas such as Kullback–Leibler divergence, Rationality and Dilemma.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Reasoning About Knowledge

Ronald Fagin;Joseph Y. Halpern;Moshe Y. Vardi;Yoram Moses.
(1995)

5466 Citations

“Sometimes” and “not never” revisited: on branching versus linear time temporal logic

E. Allen Emerson;Joseph Y. Halpern.
Journal of the ACM (1986)

1576 Citations

Knowledge and common knowledge in a distributed environment

Joseph Y. Halpern;Yoram Moses.
Journal of the ACM (1990)

1546 Citations

Reasoning about Uncertainty

Joseph Y. Halpern.
(2003)

1442 Citations

Belief, awareness, and limited reasoning

R. Fagin;J. Y. Halpern.
Artificial Intelligence (1987)

1145 Citations

A guide to completeness and complexity for modal logics of knowledge and belief

Joseph Y. Halpern;Yoram Moses.
Artificial Intelligence (1992)

1132 Citations

Gossip-based ad hoc routing

Zygmunt J. Haas;Joseph Y. Halpern;Li Li.
international conference on computer communications (2002)

1069 Citations

An analysis of first-order logics of probability

Joseph Y. Halpern.
Artificial Intelligence (1990)

871 Citations

Causes and Explanations: A Structural-Model Approach. Part I: Causes

Joseph Y. Halpern;Judea Pearl.
The British Journal for the Philosophy of Science (2005)

810 Citations

A logic for reasoning about probabilities

R. Fagin;J.Y. Halpern;N. Megiddo.
logic in computer science (1988)

792 Citations

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