Chess Game to Improve the Mental Ability of Alzheimer's Patients using A3C

Cognitive Agents' human-like reasoning is making them popular. Hence, they can aid with time-consuming jobs, complex challenges, and consumer interactions. Therefore, such technology might be better understood as a guide or assistance, speeding up and simplifying routine yet time-consuming activities. This research work explores how to use cognitive agents as an assistant for helping people (someone with a cognitive disability) to play chess by improving their brain activity and cognitive skills. Here, The Asynchronous Advantage Actor Critic (A3C) algorithm is used for training the agent about the chess game. The primary purpose of the Cognitive Agent is not to assist the player in winning games, but rather to improve the player's skills by providing the opportunity to acquire new approaches and tactics. Here, the Cognitive Agent will provide the player with information about the possible outcomes of their present line of action and provide them with a series of suggestions or guidance on the next possible moves, whether offensive or defensive. The Cognitive Agent gets activated when the Player has not made any move for some time (When the Player is unable to decide on the next move) and also when the Player's winning percentage falls dangerously below a certain threshold (When the Players course of action will definitely lead to a possible defeat outcome). The goal of this work is to help people with Alzheimer's or cognitive disabilities to learn to play chess and improve their brain activity and thinking skills.