Moving Nature-Inspired Algorithms to Parallel, Asynchronous and Decentralised Environments

This paper motivates research into implementing nature-inspired algorithms in decentralised, asynchronous and parallel environments. These characteristics typify environments such as Peer-To-Peer systems, the Grid and autonomic computing which demand robustness, decentralisation, parallelism, asynchronicity and self-organisation. Nature-inspired systems promise these properties. However, current implementations of nature-inspired systems are only loosely based on their natural counterparts. They are generally implemented as synchronous, sequential, centralised algorithms that loop through passive data structures. For their successes to be relevant to the aforementioned new computing environments, variants of these algorithms must work in truely decentralised, parallel and asynchronous MultiAgent System (MAS) environments. A general methodology is presented for engineering the transfer of nature-inspired algorithms to such a MAS framework. The concept of pheromone infrastructures is reviewed in light of emerging standards for agent platform architecture and interoperability. These ideas are illustrated using a particularly successful nature-inspired algorithm, Ant Colony System for the Travelling Salesman Problem.