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Arguments in argumentation systems cannot always be considered as standalone entities, requiring the consideration of the pieces of evidence they rely on. This evidence might have to be retrieved from external sources such as databases or the web, and each attempt to retrieve a piece of evidence comes with an associated cost. Moreover, a piece of evidence may be available in a given scenario but not in others, and this is not known beforehand. As a result, the collection of active arguments (whose entire set of evidence is available) that can be used by the argumentation machinery of the system may vary from one scenario to another. In this work, we consider an Abstract Argumentation Framework with Fallible Evidence that accounts for these issues, and propose a heuristic measure used as part of the acceptability calculus (specifically, for building pruned dialectical trees) with the aim of minimizing the evidence retrieval cost of the arguments involved in the reasoning process. We provide an algorithmic solution that is empirically tested against two baselines and formally show the correctness of our approach. [ABSTRACT FROM AUTHOR]

This work formalizes an informant-based structured argumentation approach in a multi-agent setting, where the knowledge base of an agent may include information provided by other agents, and each piece of knowledge comes attached with its informant. In that way, arguments are associated with the set of informants corresponding to the information they are built upon. Our approach proposes an informant-based notion of argument strength, where the strength of an argument is determined by the credibility of its informant agents. Moreover, we consider that the strength of an argument is not absolute, but it is relative to the resolution of the conflicts the argument is involved in. In other words, the strength of an argument may vary from one context to another, as it will be determined by comparison to its attacking arguments (respectively, the arguments it attacks). Finally, we equip agents with the means to express reasons for or against the consideration of any piece of information provided by a given informant agent. Consequently, we allow agents to argue about the arguments' strength through the construction of arguments that challenge (respectively, defeat) or are in favour of their informant agents. [ABSTRACT FROM AUTHOR]

Information-seeking interactions in multi-agent systems are required for situations in which there exists an expert agent that has vast knowledge about some topic, and there are other agents (questioners or clients) that lack and need information regarding that topic. In this work, we propose a strategy for automatic knowledge acquisition in an information-seeking setting in which agents use a structured argumentation formalism for knowledge representation and reasoning. In our approach, the client conceives the other agent as an expert in a particular domain and is committed to believe in the expert's qualified opinion about a given query. The client's goal is to ask questions and acquire knowledge until it is able to conclude the same as the expert about the initial query. On the other hand, the expert's goal is to provide just the necessary information to help the client understand its opinion. Since the client could have previous knowledge in conflict with the information acquired from the expert agent, and given that its goal is to accept the expert's position, the client may need to adapt its previous knowledge. The operational semantics for the client-expert interaction will be defined in terms of a transition system. This semantics will be used to formally prove that, once the client-expert interaction finishes, the client will have the same assessment the expert has about the performed query. [ABSTRACT FROM AUTHOR]

This paper introduces an approach for sharing beliefs in collaborative multi-agent application domains where some agents can be more credible than others. In this context, we propose a formalization where every agent has its own partial order among its peers representing the credibility the agent assigns to its informants; each agent will also have a belief base where each sentence is attached with an agent identifier which represents the credibility of that sentence. We define four different forwarding criteria for computing the credibility information for a belief to be forwarded, and for determining how the receiver should handle the incoming information; the proposal considers both the sender's and the receiver's points of view with respect to the credibility of the source of the information. [ABSTRACT FROM AUTHOR]

In the last decades, most works in the literature have been devoted to study argumentation formalisms that focus on a defeat relation among arguments. Recently, the study of a support relation between arguments regained attention among researchers; the bulk of the research has been centered on the study of support within the context of abstract argumentation by considering support as an explicit interaction between arguments. However, there exist other approaches that take support into account in a different setting. This article surveys several interpretations of the notion of support as proposed in the literature, such as deductive support, necessary support, evidential support, subargument, and backing, among others. The aim is to provide a comprehensive study where similarities and differences among these interpretations are highlighted, as well as discuss how they are addressed by different argumentation formalisms. [ABSTRACT FROM PUBLISHER]