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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A decentralised online multi-agent planning framework for multi-agent systems

Cardoso, Rafael Cau? 27 March 2018 (has links)
Submitted by PPG Ci?ncia da Computa??o (ppgcc@pucrs.br) on 2018-05-08T18:37:11Z No. of bitstreams: 1 RAFAEL_CAU?_CARDOSO_TES.pdf: 14431785 bytes, checksum: 227194ed28a9e55c3ab1fbedebf06922 (MD5) / Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2018-05-15T19:07:36Z (GMT) No. of bitstreams: 1 RAFAEL_CAU?_CARDOSO_TES.pdf: 14431785 bytes, checksum: 227194ed28a9e55c3ab1fbedebf06922 (MD5) / Made available in DSpace on 2018-05-15T19:14:18Z (GMT). No. of bitstreams: 1 RAFAEL_CAU?_CARDOSO_TES.pdf: 14431785 bytes, checksum: 227194ed28a9e55c3ab1fbedebf06922 (MD5) Previous issue date: 2018-03-27 / Sistemas multiagentes freq?entemente cont?m ambientes complexos e din?micos, nos quais os planos dos agentes podem falhar a qualquer momento durante a execu??o do sistema. Al?m disso, novos objetivos podem aparecer para os quais n?o existem nenhum plano dispon?vel. T?cnicas de planejamento s?o bem adequadas para lidar com esses problemas. H? uma quantidade extensa de pesquisa em planejamento centralizado para um ?nico agente, por?m, at? ent?o planejamento multiagente n?o foi completamente explorado na pr?tica. Plataformas multiagentes tipicamente proporcionam diversos mecanismos para coordena??o em tempo de execu??o, frequentemente necess?rios em planejamento online. Neste contexto, planejamento multiagente descentralizado pode ser eficiente e eficaz, especialmente em dom?nios fracamente acoplados, al?m de garantir algumas propriedades importantes em sistemas de agentes como privacidade e autonomia. N?s abordamos esse problema ao apresentar uma t?cnica para planejamento multiagente online que combina aloca??o de objetivos, planejamento individual utilizando rede de tarefas hier?rquicas (HTN), e coordena??o em tempo de execu??o para apoiar a realiza??o de objetivos sociais em sistemas multiagentes. Especificamente, n?s apresentamos um framework chamado Decentralised Online Multi-Agent Planning (DOMAP). Experimentos com tr?s dom?nios fracamente acoplados demonstram que DOMAP supera quatro planejadores multiagente do estado da arte com respeito a tempo de planejamento e tempo de execu??o, particularmente nos problemas mais dif?ceis. / Multi-agent systems often contain dynamic and complex environments where agents? course of action (plans) can fail at any moment during execution of the system. Furthermore, new goals can emerge for which there are no known plan available in any of the agents? plan library. Automated planning techniques are well suited to tackle both of these issues. Extensive research has been done in centralised planning for singleagents, however, so far multi-agent planning has not been fully explored in practice. Multi-agent platforms typically provide various mechanisms for runtime coordination, which are often required in online planning (i.e., planning during runtime). In this context, decentralised multi-agent planning can be efficient as well as effective, especially in loosely-coupled domains, besides also ensuring important properties in agent systems such as privacy and autonomy. We address this issue by putting forward an approach to online multi-agent planning that combines goal allocation, individual Hierarchical Task Network (HTN) planning, and coordination during runtime in order to support the achievement of social goals in multi-agent systems. In particular, we present a planning and execution framework called Decentralised Online Multi-Agent Planning (DOMAP). Experiments with three loosely-coupled planning domains show that DOMAP outperforms four other state-of-the-art multi agent planners with regards to both planning and execution time, particularly in the most difficult problems.

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