Distributed agent paradigm for soft and hard computation

This paper describes a multiagent-based simulation paradigm, for hybrid (soft and hard) simulation of complex dynamical systems. The computations are interpreted as the outcome arising out of deterministic, nondeterministic or stochastic interaction among the agents, which includes the environment. These interactions are like chemical reactions and the evolution of the multiset of agents can mimic the evolution of the complex system, e.g. genetic, nature inspired self-organized criticality and active walker (swarm and ant intelligence) models. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of the agents, so that the system evolve reaches an equilibrium (or a chaotic or an emergent) state. Practical realisation of this paradigm is achieved through a coordination programming language using Multiagent and transactions.