Application of Neurological Networks in an AI for Chess Game
Vinay Kumar, Divya Singh, Garima Bhardwaj, Ayush Bhatia
Abstract
Neurological networks in an AI is the term used for mapped networks generated by an artificial intelligence, they are inspired by the biological neural networks and are a form of connectionism a term used for model behavior and mental phenomena. These systems learn and grow by seeing or processing various examples for doing a task without actually doing specific programming for the same the network will learn and grow according to the set of instructions provided to it by the programmer and modify itself to recognize and create patterns based on the requirements. The aim is to create an ultimate chess game that can learn using image modulation techniques and play against a real human. The initial data set for learning was provided using the ultimate chess guide as well as number of games against human and itself.