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In this paper we propose a Multi-Objective Ant Colony Optimization (MOACO) algorithm called CHAC, which has been designed to solve the problem of finding the path on a map (corresponding to a simulated battlefield) that minimizes resources while maximizing safety. CHAC has been tested with two different state transition rules: an aggregative function that(More)
In this paper we compare different policies to select individuals to migrate in an island model. Our thesis is that choosing individuals in a way that exploits differences between populations can enhance diversity, and improve the system performance. This has lead us to propose a family of policies that we call multikulti, in which nodes exchange(More)
This paper investigates the behaviour of the Evolvable Agent model (EvAg) in static and dynamic environments. The EvAg is a spatially structured Genetic Algorithm (GA) designed to work on Peer-to-Peer (P2P) systems in which the population structure is a small-world graph built by newscast, a P2P protocol. Additionally to the profits in computing(More)
In a connected world, spare CPU cycles are up for grabs, if you only make its obtention easy enough. In this paper we present a distributed evolutionary computation system that uses the computational capabilities of the ubiquituous Web browser. Asynchronous Javascript and JSON (Javascript object notation, a serialization protocol) allows anybody with a Web(More)
In this paper we analyse the resilience of a Peer-to-Peer (P2P) Evolutionary Algorithm (EA) subject to the following dynamics: computing nodes acting as peers leave the system independently from each other causing a collective effect known as churn. Since the P2P EA has been designed to tackle large instances of computationally expensive problems, we will(More)
The challenge of ad-hoc computing is to find the way of taking advantage of spare cycles in an efficient way that takes into account all capabilities of the devices and inter connections available to them. In this paper we explore distributed evolutionary computation based on the Ruby on Rails framework, which overlays a Model-View-Controller on(More)
In this paper we present the Gossip-based Evolvable Agent Model (GossEvAg) within the context of parallel fine-grained Evolutionary Algorithms (EAs). It extends the Cellular Evolutionary Algorithm (CEA) definition with two novel features designed to work on Peer-to-Peer (P2P) networks: every individual is self-scheduled in a single thread and dynamically(More)
In this paper we present a distributed Evolutionary Algorithm (EA) whose population is structured using newscast, a gossiping protocol. This algorithm has been designed to deal with computation-ally expensive problems via massive scalability; therefore, we analyse the response time of the model using large instances of well-known hard optimization problems(More)
— This paper describes an Evolutionary Algorithm for evolving the decision engine of a bot designed to play the Planet Wars game. This game, which has been chosen for the Google Artificial Intelligence Challenge in 2010, requires that the artificial player is able to deal with multiple objectives, while achieving a certain degree of adaptability in order to(More)