Distributed knowledge bases : A proposal for argumentation-based semantics with cooperation

O objectivo principal desta dissertação é definir um ambiente de negociação, baseada em argumentação, para bases de conhecimento distribuídas. As bases de conhecimentos são modeladas sobre um ambiente multiagente tal que cada agente possui uma base de conhecimento própria. As bases de conhecimento dos diversos agentes podem ser independentes ou podem incluir conhecimentos comuns. O requisito mínimo para haver negociação num ambiente multiagente é que os agentes tenham a capacidade de fazer propostas, que poderão ser aceites ou rejeitadas. Numa abordagem mais sofisticada, os agentes poderão responder com contra-propostas, com o intuito de alterar aspectos insatisfatórios da pro­ posta original. Um tipo ainda mais elaborado de negociação será o baseado em argumentação. A metáfora da argumentação parece ser adequada à modelação de situações em que os diferentes agentes interagem com o propósito de determinar o significado das crenças comuns. Numa negociação baseada em argumentação, as (contra­) propostas de um agente podem ser acompanhadas de argumentos a favor da sua aceitação. Um agente poderá, então, ter um argumento aceitável para uma sua crença, se conseguir argumentar com sucesso contra os argumentos, dos outros agentes, que o atacam. Assim, as crenças de um agente caracterizam-se pela relação entre os argumentos "internos" que sustentam suas crenças, e os argumentos "externos" que sustentam crenças contraditórias de outros agentes. Portanto, o raciocínio argumentativo baseia-se na "estabilidade externa" dos argumentos aceitáveis do conjunto de agentes. Neste trabalho propõe-se uma negociação baseada em argumentação em que, para chegarem a um consenso quanto ao conhecimento comum, os agentes constroem argumentos que sustentam as suas crenças ou que se opõem aos argumentos dos agentes que as contradizem. Além disso, esta proposta lida com conhecimento incompleto (i.e., argumentos parciais) pela definição de um processo de cooperação que permite completar tal conhecimento. Assim, a negociação entre agentes é um processo argumentativo-cooperativo, em que se podem alternar os argumentos contra e a favor das crenças de um agente. Para a formação das suas crenças, a cada agente Ag está associado um conjunto Cooperate de agentes com quem coopera e um outro Argue de agentes contra quem argumenta. A negociação proposta permite a modelação de bases de conhecimento hierárquicas, representando, por exemplo, a estrutura de uma organização ou uma taxonomia nalgum domínio, e de ambientes multi-agente em que cada agente representa o conhecimento referente a um determinado período de tempo. Um agente também pode ser inquirido sobre a verdade de uma crença, dependendo a resposta do agente em questão e de quais os agentes que com ele cooperam e que a ele se opõem. Essa resposta será, no entanto, sempre consistente/ paraconsistente com as bases de conhecimento dos agentes envolvidos. Esta dissertação propõe semânticas (declarativa e operacional) da argumentação numa base de conhecimento de um agente. Partindo destas, propõe, também, semântica declarativa da negociação baseada em argumentação num ambiente multi-agente. ⓿⓿⓿ ABSTRACT: The main objective of this dissertation is to define an argumentation-based negotiation framework for distributed knowledge bases. Knowledge bases are modelling over a multi-agent setting such that each agent possibly has an independent or overlapping knowledge base. The minimum requirement for a multi-agent setting negotiation is that agents should be able to make proposals which can then either be accepted or rejected. A higher level of sophistication occurs when recipients do not just have the choice of accepting or rejecting proposals, but have the option of making counter offers to alter aspects of the proposal which are unsatisfactory. An even more elaborate kind of negotiation is argumentation-based. The argumentation metaphor seems to be adequate for modelling situations where different agents argue in order to determine the meaning of common beliefs. ln an argumentation-based negotiation, the agents are able to send justifications or arguments along with (counter) proposals indicating why they should be accepted. An argument for an agent's belief is acceptable if the agent can argue successfully against attacking arguments from other agents. Thus, agent's beliefs are characterized by the relation between its "internal" arguments supporting its beliefs and the "external" arguments supporting the contradictory beliefs of other agents. So, in a certain sense, argumentative reasoning is based on the "external stability" of acceptable arguments in the multi-agent setting. This dissertation proposes that agents evaluate arguments to obtain a consensus about a common knowledge by both proposing arguments or trying to build opposing arguments against them. Moreover, this proposal deals with incomplete knowledge (i.e. partial arguments) and so a cooperation process grants arguments to achieve knowledge completeness. Therefore, a negotiation of an agent's belief is seen as an argumentation-based process with cooperation; both cooperation and argumentation are seen as interlaced processes. Furthermore, each agent Ag has both set Argue of argumentative agents and set Cooperate of cooperative agents; every Ag must reach a consensus on its arguments with agents in Argue, and Ag may ask for arguments from agents in Cooperate to complete its partial arguments. The argumentation-based negotiation proposal allows the modelling a hierarchy of knowledge bases representing, for instance, a business's organization or a taxonomy of some subject, and also an MAS where each agent represents "acquired knowledge" in a different period of time. Furthermore, any agent in an MAS can be queried regarding the truth value of some belief. It depends on from which agent such a belief is inferred, and also what the specification in both Argue and Cooperate is, given the overall agents in the MAS. However, such an answer will always be consistent/paraconsistent with the agents' knowledge base involved. This dissertation proposes a (declarative and operational) argumentation semantics for an agent's knowledge base. Furthermore, it proposes a declarative argumentation-based negotiation semantics for a multi-agent setting, which uses most of the definitions from the former semantics

Generalizations of dung frameworks and their role in formal argumentation

This article provides a short survey of some of the most popular abstract argumentation frameworks available today. The authors present the general idea of abstract argumentation, highlighting the role of abstract frameworks in the argumentation process, and review the original Dung frameworks and their semantics. A discussion of generalizations of these frameworks follows, focusing on structures taking preferences and values into account and approaches in which not only attack but also support relations can be modeled. Finally, the authors review the concept of abstract dialectical frameworks, one of the most general systems for abstract argumentation providing a flexible, principled representation of arbitrary argument relations

Proceedings of the 11th Workshop on Nonmonotonic Reasoning

These are the proceedings of the 11th Nonmonotonic Reasoning Workshop. The aim of this series is to bring together active researchers in the broad area of nonmonotonic reasoning, including belief revision, reasoning about actions, planning, logic programming, argumentation, causality, probabilistic and possibilistic approaches to KR, and other related topics. As part of the program of the 11th workshop, we have assessed the status of the field and discussed issues such as: Significant recent achievements in the theory and automation of NMR; Critical short and long term goals for NMR; Emerging new research directions in NMR; Practical applications of NMR; Significance of NMR to knowledge representation and AI in general

Disjunctive argumentation semantics (DAS) for reasoning over distributed uncertain knowledge.

by Benson, Ng Hin Kwong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 111-117).Abstract also in Chinese.Chapter 1 --- Introduction --- p.9Chapter 1.1 --- Our approach --- p.11Chapter 1.2 --- Organization of the thesis --- p.12Chapter 2 --- Logic Programming --- p.13Chapter 2.1 --- Logic programming in Horn clauses --- p.14Chapter 2.1.1 --- Problem with incomplete information --- p.15Chapter 2.1.2 --- Problem with inconsistent information --- p.15Chapter 2.1.3 --- Problem with indefinite information --- p.16Chapter 2.2 --- Logic programming in non-Horn clauses --- p.16Chapter 2.2.1 --- Reasoning under incomplete information --- p.17Chapter 2.2.2 --- Reasoning under inconsistent information --- p.17Chapter 2.2.3 --- Reasoning under indefinite information --- p.20Chapter 2.3 --- "Coexistence of incomplete, inconsistent and indefinite information" --- p.21Chapter 2.4 --- Stable semantics --- p.22Chapter 2.5 --- Well-founded semantics --- p.23Chapter 2.6 --- Chapter summary --- p.25Chapter 3 --- Argumentation --- p.26Chapter 3.1 --- Toulmin's informal argumentation model --- p.27Chapter 3.2 --- Rescher's formal argumentation model --- p.28Chapter 3.3 --- Argumentation in AI research --- p.30Chapter 3.3.1 --- Poole's Logical Framework for Default Reasoning --- p.30Chapter 3.3.2 --- Inheritance Reasoning Framework of Touretzky et. al --- p.31Chapter 3.3.3 --- Pollock's Theory of Defeasible Reasoning --- p.32Chapter 3.3.4 --- Dung's Abstract Argumentation Framework --- p.33Chapter 3.3.5 --- Lin and Shoham's Argument System --- p.35Chapter 3.3.6 --- Vreeswijk's Abstract Argumentation --- p.35Chapter 3.3.7 --- Kowalski and Toni's Uniform Argumentation --- p.36Chapter 3.3.8 --- John Fox's Qualitative Argumentation --- p.37Chapter 3.3.9 --- Thomas Gordon's Pleading Games --- p.38Chapter 3.3.10 --- Chris Reed's Persuasive Dialogue --- p.39Chapter 3.3.11 --- Ronald Loui's Argument Game --- p.39Chapter 3.3.12 --- "Verheij's Reason-Based, Logics and CumulA" --- p.40Chapter 3.3.13 --- Prakken's Defeasible Argumentation --- p.40Chapter 3.3.14 --- Summary of existing frameworks --- p.41Chapter 3.4 --- Chapter summary --- p.42Chapter 4 --- Disjunctive Argumentation Semantics I --- p.46Chapter 4.1 --- Background --- p.47Chapter 4.2 --- Definition --- p.48Chapter 4.3 --- Conflicts within a KBS --- p.52Chapter 4.4 --- Conflicts between KBSs --- p.54Chapter 4.4.1 --- Credulous View --- p.56Chapter 4.4.2 --- Skeptical View --- p.57Chapter 4.4.3 --- Generalized Skeptical View --- p.58Chapter 4.5 --- Semantics --- p.60Chapter 4.6 --- Dialectical proof theory --- p.61Chapter 4.7 --- Relation to existing framework --- p.61Chapter 4.8 --- Issue on paraconsistency --- p.63Chapter 4.9 --- An illustrative example --- p.63Chapter 4.10 --- Chapter summary --- p.65Chapter 5 --- Disjunctive Argumentation Semantics II --- p.67Chapter 5.1 --- Background --- p.68Chapter 5.2 --- Definition --- p.70Chapter 5.2.1 --- Rules --- p.70Chapter 5.2.2 --- Splits --- p.71Chapter 5.3 --- Conflicts --- p.74Chapter 5.3.1 --- Undercut conflicts --- p.75Chapter 5.3.2 --- Rebuttal conflicts --- p.76Chapter 5.3.3 --- Thinning conflicts --- p.78Chapter 5.4 --- Semantics --- p.80Chapter 5.5 --- Relation to existing frameworks --- p.81Chapter 5.6 --- Issue on paraconsistency --- p.82Chapter 5.7 --- An illustrative example --- p.83Chapter 5.8 --- Chapter summary --- p.85Chapter 6 --- Evaluation --- p.86Chapter 6.1 --- Introduction --- p.86Chapter 6.2 --- Methodology --- p.87Chapter 6.3 --- DAS I --- p.88Chapter 6.3.1 --- Inoue's Benchmark problems --- p.88Chapter 6.3.2 --- Sherlock Holmes' problems --- p.96Chapter 6.4 --- DAS II --- p.100Chapter 6.4.1 --- Inoue's benchmark problems --- p.100Chapter 6.4.2 --- Sherlock Holmes' problem --- p.103Chapter 6.5 --- Analysis --- p.103Chapter 6.5.1 --- Possible extension --- p.104Chapter 6.6 --- Chapter summary --- p.106Chapter 7 --- Conclusion --- p.108Chapter 7.0.1 --- Possible extension of the present work --- p.109Bibliography --- p.117Chapter A --- First Oreder Logic (FOL) --- p.118Chapter B --- DAS-I Proof --- p.121Chapter B.1 --- Monotone proof --- p.121Chapter B.2 --- Soundness proof --- p.122Chapter B.3 --- Completeness proof --- p.123Chapter C --- Sherlock Holmes' Silver Blaze Excerpts --- p.125Chapter C.1 --- Double life --- p.125Chapter C.2 --- Poison stable boy --- p.12

Epistemic graphs for representing and reasoning with positive and negative influences of arguments

This paper introduces epistemic graphs as a generalization of the epistemic approach to probabilistic argumentation. In these graphs, an argument can be believed or disbelieved up to a given degree, thus providing a more fine–grained alternative to the standard Dung's approaches when it comes to determining the status of a given argument. Furthermore, the flexibility of the epistemic approach allows us to both model the rationale behind the existing semantics as well as completely deviate from them when required. Epistemic graphs can model both attack and support as well as relations that are neither support nor attack. The way other arguments influence a given argument is expressed by the epistemic constraints that can restrict the belief we have in an argument with a varying degree of specificity. The fact that we can specify the rules under which arguments should be evaluated and we can include constraints between unrelated arguments permits the framework to be more context–sensitive. It also allows for better modelling of imperfect agents, which can be important in multi–agent applications