H
Hector J. Levesque
Researcher at University of Toronto
Publications - 202
Citations - 20981
Hector J. Levesque is an academic researcher from University of Toronto. The author has contributed to research in topics: Situation calculus & Knowledge representation and reasoning. The author has an hindex of 59, co-authored 200 publications receiving 20218 citations. Previous affiliations of Hector J. Levesque include Fairchild Semiconductor International, Inc. & Canadian Institute for Advanced Research.
Papers
More filters
Proceedings Article
Towards Tractable Inference for Resource-Bounded Agents
TL;DR: A new epistemic logic is introduced, based on a three-valued version of neighborhood semantics, which allows for talking about the effort used in making inferences and is suggested that the ideas used in it could also find a role in autoepistemic reasoning.
Book ChapterDOI
The Cognitive Agents Specification Language and Verification Environment
TL;DR: This chapter describes CASL and a verification environment (CASLve) for it based on the PVS verification system, and discusses a proof that all bounded-loop CASL specifications terminate.
Book ChapterDOI
Reasoning about Noisy Sensors (and Effectors) in the Situation Calculus
TL;DR: This paper proposes a simple axiomatization that captures an agent's state of belief and the manner in which these beliefs change when actions are executed, and displays a number of intuitively reasonable properties.
Book ChapterDOI
Controlling Autonomous Robots with GOLOG
Kenneth Tam,J. Lloyd,Yves Lespérance,Hector J. Levesque,Fangzhen Lin,Daniel Marcu,Raymond Reiter,Michael Jenkin +7 more
TL;DR: By choosing an appropriate level of abstraction, one can write hardware-independent controllers for robots that perform complex navigation and reasoning tasks, by specifying a general interface through which high-level programs can interact with a variety of robotic platforms.
Proceedings Article
A first-order logic of probability and only knowing in unbounded domains
TL;DR: A new general first-order account of probability and only knowing is proposed that admits knowledge bases with incomplete and probabilistic specifications and beliefs and non-beliefs are shown to emerge as a direct logical consequence of the sentences of the knowledge base at a corresponding level of specificity.