Modeling memory as conditional phenomena for a new theory of computing

Abstract

Computers with the Von-Neumann architecture improve their processing power with the support of memory. This architecture has been improved by introducing different types of memories. The research we conduct has been inspired by the fact that humans are able to improve their memories with the support of continuous processing in the mind. It is evident that we can start with a smaller memory to drive the processing, which in turn improves, both the memory and the processing. This is analogous to how a person uses short-notes to do processing on a larger knowledge base. We postulate the processor to use the said smaller memory to access the bigger knowledge base, without the processor directly accessing the knowledge base as in the present computations. Thus we are researching into the development of the said small memory, say tactics memory, as a novel memory for Von-Neumann architecture. In doing so, we have exploited the Buddhist theory of mind, which presents everything as a phenomenon that occurs when the related conditions are met We have developed algebra for modeling the tactics memory. The tactics memory can be introduced both as a software or hardware solution for computations.