Resumen de A group selection pattern for multiagent systems and its application to grid computing
Isaac Chao Andrade
This thesis deals with groups and their self-organized management in engeenering-friendly environments, That is, the mechanism provided must prove applicable in practical settings. Groups exist in nature, in societies and in artificial systems. Individuals in biological populations organize themselves in groups. Human beings show special sociability and a tendency to become organized in groups, from 'ghettos' to firms, from neighbor associations to online communities. Participants in today's networked infrastructures (such as social networking communities in the Internet) also tend to form cliqués or groups of agents showing special preference to interact between them, partially isolated from the rest of the network. Grids are part of the next generation of networked infrastructures, which are made up not only from information but also from resources and users (human or artificial agents). Grids also organize activities around groups called Virtual Organizations. State of the art mechanisms in multiagent systems used to manage group formation (coalitions, congregations, etc) tend to be static and computationally costly, while the systems being developed in reality (grids, P2P and other overlays on top of internet) require for high adaptiveness and a dynamic view of the system. There is a need for emergent and self-organized management of the entities composing the system.
In this thesis we depart from the study of coordination and social dilemmas in multiagent systems, and we introduce a Group Selection process which, comming from Socio-biology, meets exactly the requirements mentioned above: first, it provides a mechanism by which multiagent systems incorporating high levels of uncertainty and dynamicity can be handled. Second, the mechanism implies few assumptions in agent's capabilities. In this thesis, a formalization of the Group Selection process in an engineering pattern is accomplished. Theoretical grounds in multiagent learning are provided. We propose several instantiations of the pattern in relevant coordination and social dilemma scenarios: pure coordination games, collective coordination games, prisioner's dilemma, and N-player prisoner's dilemma. As a technology application, we also provide several additional instantiations of the pattern in grid computing applications such as adaptive job scheduling, decentralized grid markets, and resource sharing policies coordination in Virtual Organizations.
The resuls of the Group Selection patern application in both multiagent systems and grid scenarios are improved cooperation and coordination, incorporating the self-organized management of the system entities and their interactions. The conclusion draw from these results is: 'Dynamically partitioning a population of agents in small groups and further co-evolving these sub-groups through Group Selection improves coordination levels in both social dilemma-based and fully cooperative multiagent systems, including grids'. This research is highly interdisciplinary by nature: Biology, Sociology, multiagent systems and grids play an important role in it. However, the Group Selection pattern as we propose it, aims to be considered a general mechanism for the engineering of multiagent systems. Biology and Sociology are the roots inspiring the pattern and grid computing is a first application, but any artificial system structured in groups could benefit from the results of
