Hybrid knowledge bases for real-time robotic reasoning

John Horst, Ernest Kent, Hassan Rifky, V. S. Subrahmanian

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations


This chapter discusses hybrid knowledge bases for real-time robotic reasoning. Complex reasoning systems in the real world need to use a number of different modes of reasoning to effectively carry out their task. This necessitates the development of techniques to represent and reason with different types of information based on different time-scales and in different forms of representation. Reasoning in complex domains requires accessing and manipulating diverse data structures as well as software to manipulate those data structures. The chapter describes a multi-level architecture for real-time intelligent reasoning in the domain of mobile robotics. Hybrid knowledge bases (HKBs) are a formalism that allow for the clean integration of multiple paradigms for representing, reasoning, and manipulating diverse forms of knowledge and data. It must be possible to reason across levels, seamlessly integrating the different types of knowledge embodied therein. The HKB paradigm forms a suitable framework to do so.

Original languageEnglish (US)
Title of host publicationMachine Intelligence and Pattern Recognition
Number of pages12
StatePublished - Jan 1 1994
Externally publishedYes

Publication series

NameMachine Intelligence and Pattern Recognition
ISSN (Print)0923-0459

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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