Toma de decisiones individuales y colectivas para sistemas multi-agente en entornos distribuidos

Esta línea de investigación se enfoca en mejorar las capacidades para la toma de decisiones individuales y colectivas de agentes en sistemas multi-agente. Dentro de este enfoque, se planea estudiar y desarrollar como mejorar en los agentes los siguientes aspectos: la capacidad de representación de conocimiento individual y colectivo, la capacidad de realizar inferencias, la capacidad de interacción e intercambio de información, y la capacidad de integrar esos elementos para tomar decisiones tanto individuales como colectivas. El aporte de esta investigación está orientado al desarrollo de formalismos y mecanismos para la toma de decisiones, por parte de agentes inteligentes deliberativos, en el contexto de un sistema multi-agente.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informática (RedUNCI

Contrastive Explanations for Argumentation-Based Conclusions

In this paper we discuss contrastive explanations for formal argumentation - the question why a certain argument (the fact) can be accepted, whilst another argument (the foil) cannot be accepted under various extension-based semantics. The recent work on explanations for argumentation-based conclusions has mostly focused on providing minimal explanations for the (non-)acceptance of arguments. What is still lacking, however, is a proper argumentation-based interpretation of contrastive explanations. We show under which conditions contrastive explanations in abstract and structured argumentation are meaningful, and how argumentation allows us to make implicit foils explicit

Formalizing dialectical explanation support for argument-based reasoning in knowledge-based systems

The concept of explanation has received attention from different areas in Computer Science, particularly in the knowledge-based systems and expert systems communities. At the same time, argumentation has evolved as a new paradigm for conceptualizing commonsense reasoning, resulting in the formalization of different argumentation frameworks and the development of several real-world argument-based applications. Although the notions of explanation and argument for a claim share many common elements in knowledge-based systems their interrelationships have not yet been formally studied in the context of the current argumentation research in Artificial Intelligence. This article explores these ideas by providing a new perspective on how to formalize dialectical explanation support for argument-based reasoning. To do this, we propose a formalization of explanations for abstract argumentation frameworks with dialectical constraints where different emerging properties are studied and analyzed. As a concrete example of the formalism introduced we show how it can be fleshed out in an implemented rule-based argumentation system.Fil: García, Alejandro Javier. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; ArgentinaFil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaFil: Rotstein, Nicolas Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaFil: Simari, Guillermo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentin

Minimality, necessity and sufficiency for argumentation and explanation

We discuss explanations for formal (abstract and structured) argumentation – the question whether and why a certain argument or claim can be accepted (or not) under various extension-based semantics. We introduce a flexible framework, which can act as the basis for many different types of explanations. For example, we can have simple or comprehensive explanations in terms of arguments for or against a claim, arguments that (indirectly) defend a claim, the evidence (knowledge base) that supports or is incompatible with a claim, and so on. We show how selection based on necessity and sufficiency can be captured in our basic framework and discuss a real-life application

A Framework for Argumentation-Based Agent Negotiation in Uncertain Settings

Automated negotiation technologies are being increasingly used in business applications, especially in the e-Commerce domain. Argumentation-Based Negotiation (ABN), among the existing approaches, has been distinguished as a powerful approach to automated negotiation due to its ability to provide more sophisticated information (arguments) that justifies and supports agents’ proposals in order to mutually influence their preference relations on the set of offers, and consequently on the negotiation outcome. During the recent years, argumentation-based negotiation has received a considerable attention in the area of agent communication. However, current proposals are mostly concerned with presenting protocols for showing how agents can interact with each other, and how arguments and offers can be generated, evaluated and exchanged under the assumption of certainty. Therefore, none of these proposals is directly targeting the agents’ uncertainty about the selection of their moves nor designing the appropriate negotiation strategies based on this uncertainty in order to help the negotiating agents better make their decisions in the negotiation settings where agents have limited or uncertain information, precluding them from making optimal individual decisions. In this thesis, we tackle the aforementioned problems by advocating an Argumentation-Based Agent Negotiation (ABAN) framework that is capable of handling the problem of agents’ uncertainty during the negotiation process. We begin by proposing an argumentation framework enriched with a new element called agent’s uncertainty as an important parameter in the agent theory to allow negotiating agents to decide which moves to play and reason about the selection of these moves under the assumption of uncertainty. Then, a method for agents’ uncertainty assessment is presented. In particular, we use Shannon entropy to assess agent’s uncertainty about their moves at each dialogue step as well as for the whole dialogue. Negotiation strategies and agent profiles issues are also explored and a methodology for designing novel negotiation strategies and agent profiles under the assumption of uncertainty is developed. Moreover, two important outcome properties namely, completeness and Nash equilibrium are discussed. Finally, the applicability of our framework is explored through several scenarios of the well-known Buyer/Seller case study. The obtained empirical results confirm the effectiveness of using our uncertainty-aware techniques and demonstrate the usefulness of using such techniques in argumentation-based negotiations

WICC 2017 : XIX Workshop de Investigadores en Ciencias de la Computación

Actas del XIX Workshop de Investigadores en Ciencias de la Computación (WICC 2017), realizado en el Instituto Tecnológico de Buenos Aires (ITBA), el 27 y 28 de abril de 2017.Red de Universidades con Carreras en Informática (RedUNCI