Chemical Reaction Optimization for population transition in peer-to-peer live streaming

Peer-to-peer (P2P) live streaming applications are very popular in recent years and a Markov open queueing network model was developed to study the population dynamics in P2P live streaming. Based on the model, we deduce an optimization problem, called population transition problem, with the objective of maximizing the probability of universal streaming by manipulating population transition probability matrix. We employ a chemical reaction-inspired metaheuristic, Chemical Reaction Optimization (CRO), to solve the problem. Simulation results show that CRO outperforms many commonly used strategies for controlling population transition in many practical P2P live streaming systems. This work also shows that CRO also demonstrates the usability of CRO to solve optimization problems. © 2010 IEEE.published_or_final_versionThe IEEE Congress on Evolutionary Computation (CEC), Barcelona, Spain, 18-23 July 2010. In Proceedings of the IEEE CEC, 2010, p. 1-

Coevolution of risk aversion, trust and trustworthiness: an agent-based approach

The research presented here deals with the evolution of personality features of humans engaged in strategic interactions. The evolution of risk aversion and trustworthiness is modelled and simulated in the context of a binary trust game, seeking the origin and end-points of an evolutionary process, accounting for different degrees of locality. This research has employed computer simulations in order to get dynamic equilibria in populations of players that keep evolving. The locality or global nature of interaction plays an important role. Risk aversion evolves together with trust and trustworthiness. Trust behaviour follows reciprocation attributes. Results of the simulations are equal to the ones elicited in empirical studies