ABAplus: Attack Reversal in Abstract and Structured Argumentation with Preferences

We present ABAplus, a system that implements reasoning with the argumentation formalism ABA+. ABA+ is a structured argumentation formalism that extends Assumption-Based Argumentation (ABA) with preferences and accounts for preferences via attack reversal. ABA+ also admits as instance Preference-based Argumentation which accounts for preferences by reversing attacks in abstract argumentation (AA). ABAplus readily implements attack reversal in both AA and ABAstyle structured argumentation. ABAplus affords computation, visualisation and comparison of extensions under five argumentation semantics. It is available both as a stand-alone system and as a web application

Método automático de clasificación de color en dientes humanos usando aprendizaje de máquina

Trabajo de InvestigaciónActualmente el proceso de identificación del color de los dientes para la fabricación de prótesis dentales es realizado manualmente por un experto que, utilizando un método de identificación visual, determina el color de las piezas dentales en la boca del paciente, usando guías de color como la VITA®. A pesar de que el método visual es el más utilizado para la identificación del color de dientes, este se ve afectado por distintas variables tales como: el cansancio del experto, la luminosidad en el ambiente, salud visual del especialista, entre otras que influyen en la identificación del color en los dientes. Los errores en la clasificación del color de los dientes pueden generar pérdidas de tiempo lo que implicaría en consecuencia sobrecostos que afectarían directamente al fabricante y la satisfacción final del cliente.1. Planteamiento del problema 2. Pregunta de investigación 3. Objetivos 4. Estado del arte 5. Marco de referencia 6. Alcances y limitaciones 7. Metodología 8. Diseño metodológico 9. Discusión y resultados 10. Conclusiones 11. Trabajos futuros 12. Bibliografía 13. ANEXOSPregradoIngeniero de Sistema

A dynamic approach for combining abstract argumentation semantics

Abstract argumentation semantics provide a direct relation from an argumentation framework to corresponding sets of acceptable arguments, or equivalently to labeling functions. Instead, we study step-wise update relations on argumentation frameworks whose fixpoints represent the labeling functions on the arguments. We make use of this dynamic approach in order to study novel ways of combining abstract argumentation semantics. In particular, we introduce the notion of a merge of two argumentation semantics, which is defined in such a way that the merge of the preferred and the grounded semantics is the complete semantics. Finally we consider how to define new semantics using the merge operator, in particular how meaningfully combine features of naive-based and complete-based semantics

On the application of answer set programming to the conference paper assignment problem

Among the tasks to be carried out by conference organizers is the one of assigning reviewers to papers. That problem is known in the literature as the Conference Paper Assignment Problem (CPAP). In this paper we approach the solution of a reasonably rich variant of the CPAP by means of Answer Set Programming (ASP). ASP is an established logic-based programming paradigm which has been successfully applied for solving complex problems arising in Artificial Intelligence. We show how the CPAP can be elegantly encoded by means of an ASP program, and we analyze the results of an experiment, conducted on real-world data, that outlines the viability of our solution