Josep Lluis de la Rosa

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Crew Intelligence Systems is a family of very simple algorithms for different classes of complex optimization problems in static and dynamic environments by means of reactive multi agent systems. Crew Intelligence systems are loosely inspired from the behavior shown by a staff of bartenders when serving drinks to customers in a bar or pub. In this paper we(More)
Current research on Virtual Organizations focuses mainly on their formation and operation phases, devoting only short references to the dissolution phase. These references typically suggest that dissolution should be obtained when the organization has fulfilled all its objectives or when it is no longer needed. This last definition is quite vague and hard(More)
We adapt the Shout and Act algorithm to Digital Objects Preservation where agents explore file systems looking for digital objects to be preserved (victims). When they find something they “shout” so that agent mates can hear it. The louder the shout, the urgent or most important the finding is. Louder shouts can also refer to closeness. We perform several(More)
A long era of exponential expansion of science seems to be ending, but we have not yet reconciled ourselves to this fact. The present social s tructure of science (that is, institutions, education, funding, publications, and so on) all evolved during this period of exponential expansion, first in the USA and the EU and now in Asian countries . This(More)
This paper presents a proposal aimed at improving the task allocation and the coordination of rescue agents in a disaster scenario. Task allocation is related to allocating victims to be rescued by each agent, while coordination is related to how these agents interact among themselves to save a larger number of victims. Rescuing lives in disasters takes(More)
Disaster rescue is one of the most serious social issues which involve very large numbers of heterogeneous rescue teams. In this paper, we introduce a co-ordination strategy for strengthening civil agents’ lives in the RoboCup-Rescue simulator scenario based on Multiple-Criteria Decision Techniques. The coordination strategy allows distributing the(More)
This paper describes an architecture named PAULA that enables coordination of autonomous agents by means of knowledge based on the agents' perception about cooperative environments. Autonomous agents are then classified into supervisor agents and physical agents. In addition, a method to improve cooperative task performance has been designed using the(More)
Our proposal is aimed at achieving reliable task allocation in cooperative agent-controlled systems by means of introspection on control-oriented features. This new approach is beneficial as it improves the way agents can coordinate with each other to perform the proposed tasks in a real cooperative environment. Introspection aims at including reliable(More)