Dominance and Equivalence for Sensor-Based Agents

Jason M. O'Kane, Steven M. LaValle

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper describes recent results from the robotics community that develop a theory, similar in spirit to the theory of computation, for analyzing sensor-based agent systems. The central element to this work is a notion of dominance of one such system over another. This relation is formally based on the agents' progression through a derived information space, but may informally be understood as describing one agent's ability to “simulate” another. We present some basic properties of this dominance relation and demonstrate its usefulness by applying it to a basic problem in robotics. We argue that this work is of interest to a broad audience of artificial intelligence researchers for two main reasons. First, it calls attention to the possibility of studying belief spaces in way that generalizes both probabilistic and nondeterministic uncertainty models. Second, it provides a means for evaluating the information that an agent is able to acquire (via its sensors and via conformant actions), independent of any optimality criterion and of the task to be completed.

Original languageEnglish (US)
Title of host publicationProceedings of the 22nd AAAI Conference on Artificial Intelligence, AAAI 2007
PublisherAmerican Association for Artificial Intelligence (AAAI) Press
Number of pages4
ISBN (Electronic)9781577353232
StatePublished - 2007
Externally publishedYes
Event22nd AAAI Conference on Artificial Intelligence, AAAI 2007 - Vancouver, Canada
Duration: Jul 22 2007Jul 26 2007

Publication series

NameProceedings of the 22nd AAAI Conference on Artificial Intelligence, AAAI 2007


Conference22nd AAAI Conference on Artificial Intelligence, AAAI 2007

ASJC Scopus subject areas

  • Artificial Intelligence


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