On Comparative Evaluation of Thorndike´s Psycho-Learning Experimental Work Versus an Optimal Swarm Intelligent System

In natural world, it is observed that some non-human biological systems show diverse learning aspects. This work presents an interesting comparative study between two naturally inspired learning systems. These are: swarm smarts intelligence for example Ant Colony System (ACS); and behavioural animal learning of Thorndike´s cat. The first ACS model used for solving optimally, Traveling Salesman Problem (TSP) by analysis of brining food from different food sources to store (in cycles) at ants´ nest. The second model, presents Thorndike´s cat behavioral learning that to get out from a cage for obtaining food. On basis of naturally observed interaction with environment, and biological brain functions, both systems have been realistically simulated using artificial neural network (ANN). Consequently, presented study motivated mainly by realistic modelling of results obtained after some non-human animal learning (ants and cats) research work.