Sobre la toma de decisiones usando razonamiento argumentativo en agentes autónomos

Desde hace mucho tiempo, la Toma de Decisiones es objeto de estudio activo en muchas áreas de investigación, como la Filosofía, Economía, Psicología, Ciencias de la Computación, entre otras. Como se discute en [29], es claro que ésta tiene tantas formas de interpretarse como áreas de estudio abordan este tema de investigación. Por ejemplo, desde una perspectiva psicológica, es necesario examinar las decisiones individuales en el contexto del conjunto de necesidades y preferencias que la gente tiene. Esto se debe a que las personas evalúan sus posibilidades basándose en la expectativa de valores subjetivos de lo que se espera de ellas. Desde una perspectiva cognitiva, la toma de decisiones es considerada como el resultado de un proceso mental en continua interacción con el ambiente, con el fin de seleccionar un curso de acción entre las alternativas posibles. El análisis normativo hace hincapié en la definición de racionalidad y en la lógica de la toma de decisiones. Alternativamente, el análisis descriptivo de la toma de decisiones concierne a las creencias y preferencias de las personas como son, y no como deberían ser. Inclusive, a otro nivel, la toma de decisiones puede concebirse como una actividad de resolución de problemas cuya finalización está dada por la obtención de una solución satisfactoria. Por lo tanto, de forma general, podría decirse que la toma de decisiones es un proceso de razonamiento (racional) o emocional (quizás irracional), y que puede estar basado en suposiciones explícitas o implícitasEje: Agentes y sistemas inteligentes. Síntesis de la tesis de igual título, presentada ante la Universidad Nacional de San Luis para obtener el título de Doctor en Ciencias de la Computación (2010).Red de Universidades con Carreras en Informática (RedUNCI

Integrating ontologies and argumentation for decision-making in breast cancer

This thesis describes some of the problems in providing care for patients with breast cancer. These are then used to motivate the development of an extension to an existing theory of argumentation, which I call the Ontology-based Argumentation Formalism (OAF). The work is assessed in both theoretical and empirical ways. From a clinical perspective, there is a problem with the provision of care. Numerous reports have noted the failure to provide uniformly high quality care, as well as the number of deaths caused by medical care. The medical profession has responded in various ways, but one of these has been the development of Decision Support Systems (DSS). The evidence for the effectiveness of such systems is mixed, and the technical basis of such systems remains open to debate. However, one basis that has been used is argumentation. An important aspect of clinical practice is the use of the evidence from clinical trials, but these trials are based on the results in defined groups of patients. Thus when we use the results of clinical trials to reason about treatments, there are two forms of information we are interested in - the evidence from trials and the relationships between groups of patients and treatments. The relational information can be captured in an ontology about the groups of patients and treatments, and the information from the trials captured as a set of defeasible rules. OAF is an extension of an existing argumentation system, and provides the basis for an argumentation-based Knowledge Representation system which could serve as the basis for future DSS. In OAF, the ontology provides a repository of facts, both asserted and inferred on the basis of formulae in the ontology, as well as defining the language of the defeasible rules. The defeasible rules are used in a process of defeasible reasoning, where monotonic consistent chains of reasoning are used to draw plausible conclusions. This defeasible reasoning is used to generate arguments and counter-arguments. Conflict between arguments is defined in terms of inconsistent formulae in the ontology, and by using existing proposals for ontology languages we are able to make use of existing proposals and technologies for ontological reasoning. There are three substantial areas of novel work: I develop an extension to an existing argumentation formalism, and prove some simple properties of the formalism. I also provide a novel formalism of the practical syllogism and related hypothetical reasoning, and compare my approach to two other proposals in the literature. I conclude with a substantial case study based on a breast cancer guideline, and in order to do so I describe a methodology for comparing formal and informal arguments, and use the results of this to discuss the strengths and weaknesses of OAF. In order to develop the case study, I provide a prototype implementation. The prototype uses a novel incremental algorithm to construct arguments and I give soundness, completeness and time-complexity results. The final chapter of the thesis discusses some general lessons from the development of OAF and gives ideas for future work

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Algorithms for computational argumentation in artificial intelligence

Argumentation is a vital aspect of intelligent behaviour by humans. It provides the means for comparing information by analysing pros and cons when trying to make a decision. Formalising argumentation in computational environment has become a topic of increasing interest in artificial intelligence research over the last decade. Computational argumentation involves reasoning with uncertainty by making use of logic in order to formalize the presentation of arguments and counterarguments and deal with conflicting information. A common assumption for logic-based argumentation is that an argument is a pair where Φ is a consistent set which is minimal for entailing a claim α. Different logics provide different definitions for consistency and entailment and hence give different options for formalising arguments and counterarguments. The expressivity of classical propositional logic allows for complicated knowledge to be represented but its computational cost is an issue. This thesis is based on monological argumentation using classical propositional logic [12] and aims in developing algorithms that are viable despite the computational cost. The proposed solution adapts well established techniques for automated theorem proving, based on resolution and connection graphs. A connection graph is a graph where each node is a clause and each arc denotes there exist complementary disjuncts between nodes. A connection graph allows for a substantially reduced search space to be used when seeking all the arguments for a claim from a given knowledgebase. In addition, its structure provides information on how its nodes can be linked with each other by resolution, providing this way the basis for applying algorithms which search for arguments by traversing the graph. The correctness of this approach is supported by theoretical results, while experimental evaluation demonstrates the viability of the algorithms developed. In addition, an extension of the theoretical work for propositional logic to first-order logic is introduced