A generalized knowledge representation system for context sensitive reasoning: Generalized HCPRs System

  • Authors:
  • Sarika Jain;N. K. Jain

  • Affiliations:
  • Department of Computer Application, CCS University, Meerut, India 250004;Department of Electronics, Zakir Husain College, University of Delhi, New Delhi, India 110002

  • Venue:
  • Artificial Intelligence Review
  • Year:
  • 2008

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Abstract

Context sensitive reasoning (i.e., changing the response of the system with change in state of any kind with respect to time, space, matter, or emotions of the system, user, or environment) is significant in real life decision-making. This is a comparatively unexplored facet of intelligent systems and needs to be looked into depth. The Extended Hierarchical Censored Production Rules (EHCPRs) System is an attempt to assemble, maintain, and employ a massive knowledge base exhibiting the property of inheritance and recognition in its reasoning along with the representation of constraints and defaults, and will facilitate all sort of possible learning schemes. Context sensitivity is addressed in the EHCPRs System that result in Generalized HCPRs (GHCPRs) System and its characteristics are exhibited through sample run of implemented system. With different context of user priorities, the GHCPRs system is shown to behave differently in its decision making.