Evaluation of Agents Interactions in a Context-Aware System

The evaluation of Multi-Agent Systems (MAS) is a complex problem and it does not have a single form. Much effort has been spent on suggesting and implementing new architectures of MAS. Often these new architectures are not even compared to any other existing architectures in order to evaluate their relative benefits. The present work focuses on interactions, the most important characteristic of any complex software as autonomous agents according to [25], as a problematic of evaluation. So, in this paper, we describe the assignment of evaluation values to Agents interaction in a specific MAS architecture. This evaluation is based on the weight of the messages brought by an interaction.Funded by projects CICYT TIN2008-06742-C02-02/TSI,CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255, and DPS2008-07029-C02-02.Publicad

La lucha contra el terrorismo y la delincuencia organizada: Una visión desde la lingüística y la ingeniería del conocimiento

The aim of Natural Language Processing is to create computational systems for the production and comprehension of language by machines. In this regard, symbolic approaches to language put forth conceptual models which represent both common and specialised knowledge. This paper describes the ontological modelling of the “collective criminal agent” and its implementation in FunGramKB, a knowledge base for language processing and artificial reasoning. More specifically, the study focuses on the conceptual definition of three terminological units from the domains of terrorism and organised crime: cartel, oriented cluster, and terrorist cell. The main assumption is that ontological modelling applied to language technologies can play a major role in combating a variety of security threats to today’s society.El objetivo del procesamiento del lenguaje natural es la creación sistemas computacionales de producción y comprensión lingüística. Un aspecto prioritario de este enfoque consiste en elaborar modelos conceptuales que permitan formalizar el conocimiento humano. Este artículo aborda la elaboración de modelos que, conteniendo unidades léxicas propias de los ámbitos del terrorismo y ladelincuencia organizada, puedan utilizarse con la base de conocimiento FunGramKB para llevar a cabo tareas de procesamiento lingüístico y de razonamiento artificial.El artículo parte del concepto “agente criminal colectivo” e ilustra la formalización conceptual de las unidades cartel (“cártel”), oriented cluster (“grupo con fines propios”) y terrorist cell (“célula terrorista”). La conceptualización de unidades léxicas constituye un paso fundamental hacia el desarrollo de aplicaciones que ofrezcan soluciones a los distintos problemas que se plantean en el ámbito profesional, así como en el conjunto de la sociedad

A multi-objective centralised agent-based optimisation approach for vehicle routing problem with unique vehicles

Motivated by heterogeneous service suppliers in crowd shipping routing problems, vehicles’ similarity assumption is questioned in the well-known logistical Vehicle Routing Problems (VRP) by considering different start/end locations, capacities, as well as shifts in the Time Window variant (VRPTW). In order to tackle this problem, a new agent-based metaheuristic architecture is proposed to capture the uniqueness of vehicles by modelling them as agents while governing the search with centralised agent cooperation. This cooperation aims to generate near optimum routes by minimising the number of vehicles used, total travelled distance, and total waiting times. The innovative architecture encapsulates three individual core modules in a flexible metaheuristic implementation. First, the problem is modelled by an agent-based module that includes its components in representing, evaluating, and altering solutions. A second metaheuristic module is then designed and integrated, followed by a multi-objective module introduced to sort solutions generated by the metaheuristic module based on Pareto dominance. Tests on benchmark instances were run, resulting in better waiting times, with an average reduction of 2.21-time units, at the expense of the other objectives. Benchmark instances are modified to tackle the unique vehicle's problem by randomising locations, capacities, and operating shifts and tested to justify the proposed model's applicability

A Semi-automated Ontology Construction for Legal Question Answering

Open Access via Springer Compact Agreement.Peer reviewedPublisher PD