Within a distributed system, autonomous agents may find it necessary to cooperate in order to achieve their objectives. Interaction protocols provide standard frameworks within which to conduct common classes of interaction, but they are only useful when the agents using them have a common interpretation of the constraints imposed by those protocols. In open systems, where there are no system-wide objectives and components are contributed from a variety of sources, this is difficult to ensure. An agent within a sufficiently complex environment will find it necessary to draw inferences from information sources of varying integrity and completeness. Given flawed or incomplete information, it may be necessary for an agent to resort to nonmonotonic reasoning in order to be able to make concrete decisions within limited windows of opportunity. This can be expected to create inconsistencies in the joint beliefs of agents which can only be repaired by dialogue between peers. To verify and repair all possible sources of inconsistency is impractical for any sizable body of inference however—any belief revision must therefore be subject to prioritisation. In this thesis, we introduce a mechanism by which agents can perform opportunistic argumentation during dialogue in order to perform distributed belief revision. An interaction portrayal uses the protocol for a given interaction to identify the logical constraints which must be resolved during the interaction as it unfolds. It then compares and reconciles the expectations of agents prior to the resolution of those constraints by generating and maintaining a system of arguments. The composition and scope of arguments is restricted in order to minimise the information exchange whilst still trying to ensure that all available admissible viewpoints are adequately represented immediately prior to any decision. This serves both to make interaction more robust (by allowing agents to make decisions based on the distributed wisdom of its peer group without being explicitly directed by a protocol) and to reconcile beliefs in a prioritised fashion (by focusing only on those beliefs which directly influence the outcome of an interaction as determined by its protocol).

JamSession foi proposto como uma plataforma para mediar e coordenar, por meio de protocolos de interação baseados em conhecimento, recursos computacionais existentes com o objetivo de compor novos serviços e desenvolver aplicações inovadoras. Entre as principais características da plataforma estão sua base formal e declarativa para permitir análise e verificação formal dos protocolos, alta performance e foco na usabilidade. A plataforma pode ser utilizada, por exemplo, na construção de ambientes inteligentes e no aprimoramento dos serviços de governo eletrônico, onde o JamSession pode atuar mediando a interação entre sistemas oferecidos por órgãos públicos visando a ampliação dos serviços oferecidos. O objetivo deste trabalho é o desenvolvimento da plataforma JamSession e sua aplicação em problemas concretos de integração e coordenação. Entre as aplicações consideradas para validar a plataforma desenvolvida estão a integração de workflows interorganizacionais e a demonstração do uso da plataforma na construção de ambientes virtuais interativos. / JamSession was proposed as a platform to mediate and coordinate, by means of knowledge-based interaction protocols, existing computational resources in order to compose new services and develop innovative applications. Among the main features of the platform are its formal and declarative foundations to provide the means for formal analysis and verification of protocols, high performance and focus on usability. The platform can be used, for instance, to build intelligent environments and to improve e-government services, where JamSession may mediate the interaction between systems offered by public agencies aiming to expand the services provided. The aim of this work is the development of JamSession platform and its application in practical demanding integration and coordination. Among the applications considered to validate the developed platform are the integration of inter-organizational workflows and its use to build interactive virtual environments.

Agent-oriented software engineering is faced with challenges that impact on the adoption of agent technology by the wider software engineering community. This is generally due to lack of adequate comprehension of the concepts of agent technology. This thesis is based on the premise that the comprehension of the concepts of and the adoption of agent technology can be improved. Two approaches are explored: the first approach is the analysis and structuring of the interactions in multiagent systems; the second approach is sharing of experiences of what works and what does not in agent-oriented software engineering using software patterns. While analysis of interactions in multiagent systems improves the understanding of the behaviour of multiagent systems, sharing multiagent system development experience improves the understanding of the concepts of agent technology as well as the challenges that face the engineering of multiagent systems. It is therefore believed that interaction analysis and experience sharing can enhance the comprehension of agent technology and hence, the adoption of the technology by the wider community of software practitioners. This thesis addresses the challenges facing agent-oriented software engineering by presenting a dedicated approach for developing agent interaction protocols to guide the interactions in a multiagent system; and a comprehensive framework for classifying, analyzing and describing agent-oriented patterns for the purpose of sharing multiagent systems development experiences.

JamSession foi proposto como uma plataforma para mediar e coordenar, por meio de protocolos de interação baseados em conhecimento, recursos computacionais existentes com o objetivo de compor novos serviços e desenvolver aplicações inovadoras. Entre as principais características da plataforma estão sua base formal e declarativa para permitir análise e verificação formal dos protocolos, alta performance e foco na usabilidade. A plataforma pode ser utilizada, por exemplo, na construção de ambientes inteligentes e no aprimoramento dos serviços de governo eletrônico, onde o JamSession pode atuar mediando a interação entre sistemas oferecidos por órgãos públicos visando a ampliação dos serviços oferecidos. O objetivo deste trabalho é o desenvolvimento da plataforma JamSession e sua aplicação em problemas concretos de integração e coordenação. Entre as aplicações consideradas para validar a plataforma desenvolvida estão a integração de workflows interorganizacionais e a demonstração do uso da plataforma na construção de ambientes virtuais interativos. / JamSession was proposed as a platform to mediate and coordinate, by means of knowledge-based interaction protocols, existing computational resources in order to compose new services and develop innovative applications. Among the main features of the platform are its formal and declarative foundations to provide the means for formal analysis and verification of protocols, high performance and focus on usability. The platform can be used, for instance, to build intelligent environments and to improve e-government services, where JamSession may mediate the interaction between systems offered by public agencies aiming to expand the services provided. The aim of this work is the development of JamSession platform and its application in practical demanding integration and coordination. Among the applications considered to validate the developed platform are the integration of inter-organizational workflows and its use to build interactive virtual environments.

Past research on multi-agent simulation with cooperative reinforcement learning (RL) for homogeneous agents focuses on developing sharing strategies that are adopted and used by all agents in the environment. These sharing strategies are considered to be reciprocating because all participating agents have a predefined agreement regarding what type of information is shared, when it is shared, and how the participating agent's policies are subsequently updated. The sharing strategies are specifically designed around manipulating this shared information to improve learning performance. This thesis targets situations where the assumption of a single sharing strategy that is employed by all agents is not valid. This work seeks to address how agents with no predetermined sharing partners can exploit groups of cooperatively learning agents to improve learning performance when compared to Independent learning. Specifically, several intra-agent methods are proposed that do not assume a reciprocating sharing relationship and leverage the pre-existing agent interface associated with Q-Learning to expedite learning. The other agents' functions and their sharing strategies are unknown and inaccessible from the point of view of the agent(s) using the proposed methods. The proposed methods are evaluated on physically embodied agents in the multi-agent cooperative robotics field learning a navigation task via simulation. The experiments conducted focus on the effects of the following factors on the performance of the proposed non-reciprocating methods: scaling the number of agents in the environment, limiting the communication range of the agents, and scaling the size of the environment. / Master of Science

Le travail que nous présentons dans cette thèse s'articule autour du problème de la formation de coalitions entre des agents égoïstes qui planifient leurs activités, dans les systèmes multi-agents (SMA). Nous avons proposé, dans un premier temps, un mécanisme qui se fonde sur l’analyse des actions des agents dans leurs plans et le raisonnement sur les plans des autres, grâce notamment au calcul d’un degré de croyance sur les actions. Nous nous sommes, par ailleurs, intéressés au problème de la formation de coalitions avec des contraintes dynamiques et des préférences que les agents révèlent et communiquent aux autres lors de leurs négociations. Enfin, nous avons affiné notre mécanisme de formation des coalitions en permettant une recherche des coalitions guidée par la construction d'un arbre de contraintes et d'un arbre de coalitions, qui sont ensuite exploré par le biais de l'algorithme Monte-Carlo. / The work we present, in this thesis, focuses on the coalition formation problem for self-interested agents which plan their activities in multi-agents systems. As a first step, we have proposed, a mechanism that is based on the analysis of the agents' actions in their plans and reasoning about the plans of others. Additionally, we have addressed the problem of coalition formation with dynamic constraints and preferences that agents reveal and communicate to others during their negotiations. Finally, we have refined our coalition formation mechanism allowing a guided search of the coalitions by building a tree of constraints and a tree of coalitions. Each tree is explored by means of the Monte-Carlo algorithm.