Grounding Mundane Inference in Perception

Ian D Horswill*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We describe a uniform technique for representing both sensory data and the attentional state of an agent using a subset of modal logic with indexicals. The resulting representation maps naturally into feed-forward parallel networks or can be implemented on stock hardware using bit-mask instructions. The representation has "circuit-semantics" (Nilsson, 1994, Rosenschein and Kaelbling, 1986), but can efficiently represent propositions containing modals, unary predicates, and functions. We describe an example using Kludge, a vision-based mobile robot programmed to perform simple natural language instructions involving fetching and following tasks.

Original languageEnglish (US)
Pages (from-to)63-77
Number of pages15
JournalAutonomous Robots
Volume5
Issue number1
DOIs
StatePublished - 1998

Keywords

  • Active perception
  • Agent architectures
  • Knowledge representation
  • Reasoning
  • Vision

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Grounding Mundane Inference in Perception'. Together they form a unique fingerprint.

Cite this