Understanding of Collective Decision-Making in Natural Swarms System, Applications and Challenges

Abstract

Swarm robotics is an emergent field that is inspired from biological system. Decentralized control for the achievement of global task. The concept of collective system is used to develop artificial systems that can perform the tasks in a collective manner, with minimum resources. In this paper we have presented group level intelligence to achieve global goals. Optimization strategies for swarm robotics, self-learning of agents by using trial and error, a well know technique of reinforcement learning and how system is designed to minimize the task allocation. We discuss some of the enabling factors at micro and macro-level and how these factors affect the modelling and intelligence of artificial system. Using the modern artificial intelligence, designing new systems to solve the complex research problems. And some of the key challenges in the field of swarm intelligence.