Learning techniques in Extended Hierarchical Censored Production Rules (EHCPRs) System
EHCPRs system is an intelligent system for knowledge representation and reasoning with all the possible learning methods incorporated in it. In such a system an EHCPR is used as a unit of knowledge for representing any concept independent of its application domain. There are a number of EHCPRs at various levels of hierarchy connected to each other via a number of operators, hence resulting in a knowledge structure of hierarchical network of EHCPRs. This EHCPRs network has the capability of continuous expansion through new added EHCPRs at proper place of the hierarchy as well as these already acquired EHCPRs are subject to continuous refinement with time. The EHCPRs tree in the network will become stronger in terms of strength of implication and richer in knowledge with time. This paper discusses different learning schemes possible for enhancing the knowledge base and the database of the EHCPRs system. The EHCPRs System is made to learn so that it is able to serve the multilingual global community. The online EHCPRs system will open all new avenues of learning methods in the system.