Distributed Computation using Evolutionary Consciousness : An Approach

Abstract

The modeling of biological phenomena and its adaptations to distributed computing are promising research areas. The computational modeling of neurobiological phenomena, such as cognition and consciousness, has potential for applications into bio-inspired distributed computing. The functioning of neurological structures is inherently distributed in nature having a closer match to distributed computing. This paper proposes a mathematical model of state of consciousness by following the functional neurophysiology as well as elements of distributed computing. The scopes of evolution of consciousness and memory are incorporated into the model. The nodal classifications and formation of structural hierarchy in distributed computing nodes by incorporating elements of cognitive model are investigated. Evaluation of the model is made by numerical simulation considering different choice functions. The results illustrate that, model of consciousness can be adapted to bio-inspired distributed computing structures and the gradual evolution of consciousness is deterministic under fair excitations from environment.

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“…The model showcases its adaptability to bio-inspired distributed computing structures through numerical simulations using various choice functions. His work suggests that the model shows promise in its application to bio-inspired structures and that the development of consciousness is influenced by various environmental stimuli [128]. Understanding and addressing classification problems is a crucial focus in the field of machine learning [129].…”