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

A Parameterised Hierarchy of Argumentation Semantics for Extended Logic Programming and its Application to the Well-founded Semantics

Argumentation has proved a useful tool in defining formal semantics for assumption-based reasoning by viewing a proof as a process in which proponents and opponents attack each others arguments by undercuts (attack to an argument's premise) and rebuts (attack to an argument's conclusion). In this paper, we formulate a variety of notions of attack for extended logic programs from combinations of undercuts and rebuts and define a general hierarchy of argumentation semantics parameterised by the notions of attack chosen by proponent and opponent. We prove the equivalence and subset relationships between the semantics and examine some essential properties concerning consistency and the coherence principle, which relates default negation and explicit negation. Most significantly, we place existing semantics put forward in the literature in our hierarchy and identify a particular argumentation semantics for which we prove equivalence to the paraconsistent well-founded semantics with explicit negation, WFSX$_p$. Finally, we present a general proof theory, based on dialogue trees, and show that it is sound and complete with respect to the argumentation semantics.Comment: To appear in Theory and Practice of Logic Programmin

Defeasible Argumentation for Cooperative Multi-Agent Planning

Tesis por compendio[EN] Multi-Agent Systems (MAS), Argumentation and Automated Planning are three lines of investigations within the field of Artificial Intelligence (AI) that have been extensively studied over the last years. A MAS is a system composed of multiple intelligent agents that interact with each other and it is used to solve problems whose solution requires the presence of various functional and autonomous entities. Multi-agent systems can be used to solve problems that are difficult or impossible to resolve for an individual agent. On the other hand, Argumentation refers to the construction and subsequent exchange (iteratively) of arguments between a group of agents, with the aim of arguing for or against a particular proposal. Regarding Automated Planning, given an initial state of the world, a goal to achieve, and a set of possible actions, the goal is to build programs that can automatically calculate a plan to reach the final state from the initial state. The main objective of this thesis is to propose a model that combines and integrates these three research lines. More specifically, we consider a MAS as a team of agents with planning and argumentation capabilities. In that sense, given a planning problem with a set of objectives, (cooperative) agents jointly construct a plan to satisfy the objectives of the problem while they defeasibly reason about the environmental conditions so as to provide a stronger guarantee of success of the plan at execution time. Therefore, the goal is to use the planning knowledge to build a plan while agents beliefs about the impact of unexpected environmental conditions is used to select the plan which is less likely to fail at execution time. Thus, the system is intended to return collaborative plans that are more robust and adapted to the circumstances of the execution environment. In this thesis, we designed, built and evaluated a model of argumentation based on defeasible reasoning for planning cooperative multi-agent system. The designed system is independent of the domain, thus demonstrating the ability to solve problems in different application contexts. Specifically, the system has been tested in context sensitive domains such as Ambient Intelligence as well as with problems used in the International Planning Competitions.[ES] Dentro de la Inteligencia Artificial (IA), existen tres ramas que han sido ampliamente estudiadas en los últimos años: Sistemas Multi-Agente (SMA), Argumentación y Planificación Automática. Un SMA es un sistema compuesto por múltiples agentes inteligentes que interactúan entre sí y se utilizan para resolver problemas cuya solución requiere la presencia de diversas entidades funcionales y autónomas. Los sistemas multiagente pueden ser utilizados para resolver problemas que son difíciles o imposibles de resolver para un agente individual. Por otra parte, la Argumentación consiste en la construcción y posterior intercambio (iterativamente) de argumentos entre un conjunto de agentes, con el objetivo de razonar a favor o en contra de una determinada propuesta. Con respecto a la Planificación Automática, dado un estado inicial del mundo, un objetivo a alcanzar, y un conjunto de acciones posibles, el objetivo es construir programas capaces de calcular de forma automática un plan que permita alcanzar el estado final a partir del estado inicial. El principal objetivo de esta tesis es proponer un modelo que combine e integre las tres líneas anteriores. Más específicamente, nosotros consideramos un SMA como un equipo de agentes con capacidades de planificación y argumentación. En ese sentido, dado un problema de planificación con un conjunto de objetivos, los agentes (cooperativos) construyen conjuntamente un plan para resolver los objetivos del problema y, al mismo tiempo, razonan sobre la viabilidad de los planes, utilizando como herramienta de diálogo la Argumentación. Por tanto, el objetivo no es sólo obtener automáticamente un plan solución generado de forma colaborativa entre los agentes, sino también utilizar las creencias de los agentes sobre la información del contexto para razonar acerca de la viabilidad de los planes en su futura etapa de ejecución. De esta forma, se pretende que el sistema sea capaz de devolver planes colaborativos más robustos y adaptados a las circunstancias del entorno de ejecución. En esta tesis se diseña, construye y evalúa un modelo de argumentación basado en razonamiento defeasible para un sistema de planificación cooperativa multiagente. El sistema diseñado es independiente del dominio, demostrando así la capacidad de resolver problemas en diferentes contextos de aplicación. Concretamente el sistema se ha evaluado en dominios sensibles al contexto como es la Inteligencia Ambiental y en problemas de las competiciones internacionales de planificación.[CA] Dins de la intel·ligència artificial (IA), hi han tres branques que han sigut àmpliament estudiades en els últims anys: Sistemes Multi-Agent (SMA), Argumentació i Planificació Automàtica. Un SMA es un sistema compost per múltiples agents intel·ligents que interactúen entre si i s'utilitzen per a resoldre problemas la solución dels quals requereix la presència de diverses entitats funcionals i autònomes. Els sistemes multiagente poden ser utilitzats per a resoldre problemes que són difícils o impossibles de resoldre per a un agent individual. D'altra banda, l'Argumentació consistiex en la construcció i posterior intercanvi (iterativament) d'arguments entre un conjunt d'agents, amb l'objectiu de raonar a favor o en contra d'una determinada proposta. Respecte a la Planificació Automàtica, donat un estat inicial del món, un objectiu a aconseguir, i un conjunt d'accions possibles, l'objectiu és construir programes capaços de calcular de forma automàtica un pla que permeta aconseguir l'estat final a partir de l'estat inicial. El principal objectiu d'aquesta tesi és proposar un model que combine i integre les tres línies anteriors. Més específicament, nosaltres considerem un SMA com un equip d'agents amb capacitats de planificació i argumentació. En aquest sentit, donat un problema de planificació amb un conjunt d'objectius, els agents (cooperatius) construeixen conjuntament un pla per a resoldre els objectius del problema i, al mateix temps, raonen sobre la viabilitat dels plans, utilitzant com a ferramenta de diàleg l'Argumentació. Per tant, l'objectiu no és només obtindre automàticament un pla solució generat de forma col·laborativa entre els agents, sinó també utilitzar les creences dels agents sobre la informació del context per a raonar sobre la viabilitat dels plans en la seua futura etapa d'execució. D'aquesta manera, es pretén que el sistema siga capaç de tornar plans col·laboratius més robustos i adaptats a les circumstàncies de l'entorn d'execució. En aquesta tesi es dissenya, construeix i avalua un model d'argumentació basat en raonament defeasible per a un sistema de planificació cooperativa multiagent. El sistema dissenyat és independent del domini, demostrant així la capacitat de resoldre problemes en diferents contextos d'aplicació. Concretament el sistema s'ha avaluat en dominis sensibles al context com és la inte·ligència Ambiental i en problemes de les competicions internacionals de planificació.Pajares Ferrando, S. (2016). Defeasible Argumentation for Cooperative Multi-Agent Planning [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/60159TESISCompendi

Argumentation for machine learning: a survey

Existing approaches using argumentation to aid or improve machine learning differ in the type of machine learning technique they consider, in their use of argumentation and in their choice of argumentation framework and semantics. This paper presents a survey of this relatively young field highlighting, in particular, its achievements to date, the applications it has been used for as well as the benefits brought about by the use of argumentation, with an eye towards its future

Context-Aware Multi-Agent Planning in intelligent environments

A system is context-aware if it can extract, interpret and use context information and adapt its functionality to the current context of use. Multi-agent planning generalizes the problem of planning in domains where several agents plan and act together, and share resources, activities, and goals. This contribution presents a practical extension of a formal theoretical model for Context-Aware Multi-Agent Planning based upon an argumentationbased defeasible logic. Our framework, named CAMAP, is implemented on a platform for open multiagent systems and has been experimentally tested, among others, in applications of ambient intelligence in the field of health-care. CAMAP is based on a multi-agent partial-order planning paradigm in which agents have diverse abilities, use an argumentation-based defeasible contextual reasoning to support their own beliefs and refute the beliefs of the others according to their context knowledge during the plan search process. CAMAP shows to be an adequate approach to tackle ambient intelligence problems as it gathers together in a single framework the ability of planning while it allows agents to put forward arguments that support or argue upon the accuracy, unambiguity and reliability of the context-aware information.This work is mainly supported by the Spanish Ministry of Science and Education under the FPU Grant Reference AP2009-1896 awarded to Sergio Pajares Ferrando, and Projects, TIN2011-27652-C03-01, and Consolider Ingenio 2010 CSD2007-00022.Pajares Ferrando, S.; Onaindia De La Rivaherrera, E. (2013). Context-Aware Multi-Agent Planning in intelligent environments. Information Sciences. 227:22-42. https://doi.org/10.1016/j.ins.2012.11.021S224222

Agent based simulation for group formation

Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made just by one individual. The simulation of group decision making through a Multi-Agent System is a very interesting research topic. The purpose of this paper it to specify the actors involved in the simulation of a group decision, to present a model to the process of group formation and to describe the approach made to implement that model. In the group formation model it is considered the existence of incomplete and negative information, which was identified as crucial to make the simulation closer to the reality

Defeasible-argumentation-based multi-agent planning

[EN] This paper presents a planning system that uses defeasible argumentation to reason about context information during the construction of a plan. The system is designed to operate in cooperative multi-agent environments where agents are endowed with planning and argumentation capabilities. Planning allows agents to contribute with actions to the construction of the plan, and argumentation is the mechanism that agents use to defend or attack the planning choices according to their beliefs. We present the formalization of the model and we provide a novel specification of the qualification problem. The multi-agent planning system, which is designed to be domain-independent, is evaluated with two planning tasks from the problem suites of the International Planning Competition. We compare our system with a non-argumentative planning framework and with a different approach of planning and argumentation. The results will show that our system obtains less costly and more robust solution plans.This work has been partly supported by the Spanish MINECO under project TIN2014-55637-C2-2-R and the Valencian project PROMETEO II/2013/019.Pajares Ferrando, S.; Onaindia De La Rivaherrera, E. (2017). Defeasible-argumentation-based multi-agent planning. Information Sciences. 411:1-22. https://doi.org/10.1016/j.ins.2017.05.014S12241

Dispute Resolution Using Argumentation-Based Mediation

Mediation is a process, in which both parties agree to resolve their dispute by negotiating over alternative solutions presented by a mediator. In order to construct such solutions, mediation brings more information and knowledge, and, if possible, resources to the negotiation table. The contribution of this paper is the automated mediation machinery which does that. It presents an argumentation-based mediation approach that extends the logic-based approach to argumentation-based negotiation involving BDI agents. The paper describes the mediation algorithm. For comparison it illustrates the method with a case study used in an earlier work. It demonstrates how the computational mediator can deal with realistic situations in which the negotiating agents would otherwise fail due to lack of knowledge and/or resources.Comment: 6 page

Supporting communication among cognitive robots in simulated environments

Despite the fact that the Khepera II is an experimental platform widely used in the scientific community related to robotics research, its application to cognitive robotics is not as extensive as it should be. Particularly, in this field of research, the Khe-DeLP framework has arisen as an interesting proposal for developing cognitive agents to control real and simulated Khepera II robots. Although Khe-DeLP allows to work with multiple robots within the same environment, at present, only nonintentional communication among them can be achieved in this framework. Therefore, in this work we present extentions to Khe-DeLP to be able to model simulated scenarios where multiple robots interact by using explicit communication among them. This new feature improves Khe-DeLP since any kind of coordination problems can be simulated within the framework. As concept test, an example is presented which aims to validate coordinated behaviours of the robots by using the new communication features included in Khe-DeLP.Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Argument-based negotiation among BDI agents

Negotiation is a basic mechanism for interaction that allows the members in a Multiagent System to coordinate their actions and to reach a favorable agreement. When agents are collaborative, the negotiation process progresses through a dialogue in which proposals and counter-proposals are exchanged in a common effort to advance towards a mutual agreement. An Interaction Protocol regulates communication and gives structure to the dialog. Most interaction protocols designed to regulate negotiation among agents are abstract models based in some real world negotiation practice (e.g. auctions). Here we propose a deliberative mechanism for negotiation among BDI agents based in Argumentation.Facultad de Informátic