Alejandro Rosete

Testing in Agent Oriented Methodologies

Testing is an important activity in software development in order to assure the correctness of software. However, testing is often disregarded in most agent oriented methodologies, mainly because they focus on analysis and design activities, and consider that implementation and testing issues can be performed using traditional techniques. But multi-agent systems implementation has some features that make it distinctive from traditional software. This paper presents an overview of testing in agent orientation based on the V-Model in order to establish the role of testing activities in an agent oriented development lifecycle. It also identifies how different types of testing are covered by previous work and the directions for further work.

Fuzzy constraints in the Truck and Trailer Routing Problem

Techniques based on Soft Computing are useful to solve real-world problems where decision makers use subjective knowledge when making decisions. In many problems in transport and logistics it is necessary to take into account that the available knowledge about the problem is imprecise or uncertain. Truck and Trailer Routing Problem (TTRP) is one of most recent and interesting problems in transport routing planning. Most of models used in the literature assume that the data available are accurate; for this reason it would be appropriate to focus research toward defining TTRP models for incorporating the uncertainty present in their data.

Patrones de implementación para incluir comportamientos proactivos

La programacion orientada a objeto enfrenta retos como es el desarrollo de software en ambientes distribuidos. En esta linea ha surgido el paradigma de agentes. Un agente exhibe comportamientos que lo diferencia de un objeto, como la autonomia y la proactividad. La proactividad permite desarrollar sistemas dirigidos por metas, en los que no es necesaria una peticion para que se inicie un trabajo. Incorporar proactividad a un software es hoy una necesidad, existe una gran dependencia de los sistemas computarizados y es mayor la delegacion de tareas en ellos. Los patrones se han utilizado con exito en la reduccion de tiempo de desarrollo y el numero de errores en el desarrollo de software, ademas de ser una guia para resolver un problema tipico. En este trabajo se presentan dos patrones de implementacion para incorporar proactividad en un software y facilitar el trabajo con los agentes. Se incluye un caso de estudio del uso de los patrones propuestos en un observatorio tecnologico

Consensus-based journal rankings: A complementary tool for bibliometric evaluation

Annual journal rankings are usually considered a tool for the evaluation of research and researchers. Although they are an objective resource for such evaluation, they also present drawbacks: (a) the uncertainty about the definite position of a target journal in the corresponding annual ranking when selecting a journal, and (b) in spite of the nonsignificant difference in score (for instance, impact factor) between consecutive journals in the ranking, the journals are strictly ranked and eventually placed in different terciles/quartiles, which may have a significant influence in the subsequent evaluation. In this article we present several proposals to obtain an aggregated consensus ranking as an alternative/complementary tool to standardize annual rankings. To illustrate the proposed methodology we use as a case study the Journal Citation Reports, and in particular the category of Computer Science: Artificial Intelligence (CS:AI). In the context of the consensus rankings obtained by the different methods, we discuss the convenience of using one or the other procedure according to the corresponding framework. In particular, our proposals allow us to obtain consensus rankings that avoid crisp frontiers between similarly ranked journals and consider the longitudinal/temporal evolution of the journals.

Mining Medical Data to Obtain Fuzzy Predicates

The collection of methods known as ‘data mining’ offers methodological and technical solutions to deal with the analysis of medical data and the construction of models. Medical data have a special status based upon their applicability to all people; their urgency (including life-or death); and a moral obligation to be used for beneficial purposes. Due to this reality, this article addresses the special features of data mining with medical data. Specifically, we will apply a recent data mining algorithm called FuzzyPred. It performs an unsupervised learning process to obtain a set of fuzzy predicates in a normal form, specifically conjunctive (CNF) and disjunctive normal form (DNF). Experimental studies in known medical datasets shows some examples of knowledge that can be obtained by using this method. Several kind of knowledge that was obtained by FuzzyPred in these databases cannot be obtained by other popular data mining techniques.

An Agent Based Implementation of Proactive S-Metaheuristics

This paper presents the use of a multi-agent system for the development of proactive S-Metaheuristics (i.e. single-solution based metaheuristics) derived from Record-to-Record Travel (RRT) and Local Search. The basic idea is to implement metaheuristics as agents that operate in the environment of the optimization process with the goal of avoiding stagnation in local optima by adjusting their parameters and neighborhood. Environmental information about previous solutions is used to determine the best operators and parameters. The proactive adjustment of the neighborhood is based on the identification of the best operators using Fitness Distance Correlation (FDC). The proactive adjustment of the parameters is focused on guarantying a minimal level of acceptance of new solutions. Besides, a simple form of combination of both proactive behaviors is introduced. The system has been validated through experimentation with 28 functions on binary strings.

FSS-OBOP: Feature subset selection guided by a bucket order consensus ranking

Several authors have ton the importance of aggregating the results of different feature selection methods in order to improve the solutions obtained. To the best of our knowledge, the consensus rankings obtained in all of these proposals do not allow that some variables are tied. This paper studies the advantages of allowing ties in the consensus ranking obtained from aggregating several features selection methods. This implies that the consensus ranking is modeled as the problem of obtaining the Optimal Bucket Order instead of solving the Rank Aggregation Problem. In this paper we propose a filter-wrapper algorithm, that we will call FSS-OBOP, which uses a filter-based consensus ranking with ties to guide the posterior wrapper phase. By using a benchmark with 12 high-dimensional datasets, we show that allowing ties in the consensus rankings leads to subsets that, when used to induce a classifier, obtain at least the same, when not better, accuracy. Furthermore, and what is actually more significant, they reduce the number of wrapper evaluations extraordinarily.

Sign Languague Recognition Without Frame-Sequencing Constraints: A Proof of Concept on the Argentinian Sign Language

Automatic sign language recognition (SLR) is an important topic within the areas of human-computer interaction and machine learning. On the one hand, it poses a complex challenge that requires the intervention of various knowledge areas, such as video processing, image processing, intelligent systems and linguistics. On the other hand, robust recognition of sign language could assist in the translation process and the integration of hearing-impaired people, as well as the teaching of sign language for the hearing population.

Solving a Multiobjective Truck and Trailer Routing Problem with Fuzzy Constraints

The Truck and Trailer Routing Problem uses trucks pulling trailers as a distinctive feature of the Vehicle Routing Problem. Recently, this problem has been treated considering the capacity constraints as fuzzy. This situation means that the decision maker admits the violation of these constraints according to a value of tolerance. This relaxation can generate a set of solutions with very low costs but its non-fulfillment grade of the capacity constraints can be high and vice versa. This fuzzy variant is generalized in this work from a multiobjective approach by incorporating an objective to minimize the violation of constraints. We present and discuss the computational experiments carried out to solve the multiobjective Truck and Trailer Routing Problem with fuzzy constraint using benchmark instances with sizes ranging from 50 to 199 customers.

An agent based approach for the implementation of cooperative proactive S-Metaheuristics

This paper introduces several cooperative proactive S-Metaheuristics.The proposal is based on two characteristics of agents: proactivity and cooperation.Proactive S-Metaheuristics avoid local optima by adjusting parameters and operators.Simple forms of cooperation are used to combine proactive metaheuristics.The experiments consider binary problems, knapsack and travelling salesman problems. This paper introduces several cooperative proactive S-Metaheuristics, i.e. single-solution based metaheuristics, which are implemented taking advantage of two singular characteristics of the agent paradigm: proactivity and cooperation. Proactivity is applied to improve traditional versions of Threshold Accepting and Great Deluge Algorithm metaheuristics. This approach follows previous work for the definition of proactive versions of the Record-to-Record Travel and Local Search metaheuristics. Proactive metaheuristics are implemented as agents that cooperate in the environment of the optimization process with the goal of avoiding stagnation in local optima by adjusting their parameters. Based on the environmental information about previous solutions, the proactive adjustment of the parameters is focused on keeping a minimal level of acceptance for the new solutions. In addition, simple forms of cooperation by competition are used to develop cooperative metaheuristics based on the combination of the four proactive metaheuristics. The proposed metaheuristics have been validated through experimentation with 28 benchmark functions on binary strings, and several instances of knapsack problems and travelling salesman problems.