Modelado basado en agentes para el estudio de sistemas complejos

El modelado basado en agentes es una herramienta que en las dos últimas décadas está siendo cada vez más utilizada para el estudio de sistemas complejos en distintos ámbitos de las ciencias sociales y como ayuda para la toma de decisiones. Las entidades de los sistemas sociales pueden ser modeladas como agentes autónomos que interaccionan en un entorno. Estos modelos se pueden simular para analizar el comportamiento que muestra el sistema en distintos escenarios y configuraciones. En este artículo se ilustra su aplicación con varios casos, y se describen las herramientas más utilizadas actualmente, así como los retos metodológicos para su utilización en gran escalaproyectos CSD2010-00034 (CONSOLIDER-INGENIO 2010) y TIN2011-28335-C02-01 subvencionados por el Gobierno de España con referencias, y el proyecto GREX251-2009 subvencionado por la Junta de Castilla y León

Knowledge Transfer in Commercial Feature Extraction for the Retail Store Location Problem

Location is the most important strategic decision in retailing. The location problem is markedly complex and multicriteria. One of the key factors to consider is the so-called balanced tenancy —i.e., the degree to which neighboring businesses complement each other. There are several network-based methodologies that formalize the notion of balanced tenancy by capturing the spatial interactions between different commercial sectors in cities. Some of these methodologies provide indices that have been successfully used as input features in location recommendation systems. However, from a predictive perspective, it is still unknown which of the indices provides best results. In this work, we analyze the performance of six of these indices on a set of nine Spanish cities. Our results show that the combined use of all of them in an ensemble model such as random forest significantly improves predictive accuracy. In addition, we explore the effect of knowledge transfer between cities from two different perspectives: 1) quantify how much the quality of solutions degrades when the balanced tenancy of a city is explored through the indices obtained from another city; 2) investigate the interest of network consensus approaches for knowledge transfer in retailing.Spanish Ministry of Science, Innovation and Universities through Excellence Network under Grant RED2018-102518-T, in part by the Spanish State Research Agency under Grant PID2020-118906GB-I00/AEI/10.13039/501100011033, and in part by the Junta de Castilla y León Consejería de Educación under Grant BDNS 425389

Comparative study of classification algorithms for quality assessment of resistance spot welding joints from preand post-welding inputs

Resistance spot welding (RSW) is a widespread manufacturing process in the automotive industry. There are different approaches for assessing the quality level of RSW joints. Multi-input-single-output methods, which take as inputs either the intrinsic parameters of the welding process or ultrasonic nondestructive testing variables, are commonly used. This work demonstrates that the combined use of both types of inputs can significantly improve the already competitive approach based exclusively on ultrasonic analyses. The use of stacking of tree ensemble models as classifiers dominates the classification results in terms of accuracy, F-measure and area under the receiver operating characteristic curve metrics. Through variable importance analyses, the results show that although the welding process parameters are less relevant than the ultrasonic testing variables, some of the former provide marginal information not fully captured by the latter

Explainable machine learning for project management control

Project control is a crucial phase within project management aimed at ensuring —in an integrated manner— that the project objectives are met according to plan. Earned Value Management —along with its various refinements— is the most popular and widespread method for top-down project control. For project control under uncertainty, Monte Carlo simulation and statistical/machine learning models extend the earned value framework by allowing the analysis of deviations, expected times and costs during project progress. Recent advances in explainable machine learning, in particular attribution methods based on Shapley values, can be used to link project control to activity properties, facilitating the interpretation of interrelations between activity characteristics and control objectives. This work proposes a new methodology that adds an explainability layer based on SHAP —Shapley Additive exPlanations— to different machine learning models fitted to Monte Carlo simulations of the project network during tracking control points. Specifically, our method allows for both prospective and retrospective analyses, which have different utilities: forward analysis helps to identify key relationships between the different tasks and the desired outcomes, thus being useful to make execution/replanning decisions; and backward analysis serves to identify the causes of project status during project progress. Furthermore, this method is general, model-agnostic and provides quantifiable and easily interpretable information, hence constituting a valuable tool for project control in uncertain environments

Let’s go fishing: A quantitative analysis of subsistence choices with a special focus on mixed economies among small-scale societies

The transition to agriculture is regarded as a major turning point in human history. In the present contribution we propose to look at it through the lens of ethnographic data by means of a machine learning approach. More specifically, we analyse both the subsistence economies and the socioecological context of 1290 societies documented in the Ethnographic Atlas with a threefold purpose: (i) to better understand the variability and success of human economic choices; (ii) to assess the role of environmental settings in the configuration of the different subsistence economies; and (iii) to examine the relevance of fishing in the development of viable alternatives to cultivation. All data were extracted from the publicly available cross-cultural database D-PLACE. Our results suggest that not all subsistence combinations are viable, existing just a subset of successful economic choices that appear recurrently in specific ecological systems. The subsistence economies identified are classified as either primary or mixed economies in accordance with an information-entropy-based quantitative criterion that determines their degree of diversification. Remarkably, according to our results, mixed economies are not a marginal choice, as they constitute 25% of the cases in our data sample. In addition, fishing seems to be a key element in the configuration of mixed economies, as it is present across all of them.Spanish Ministry of Science and Innovation: Excellence Networks (HAR2017-90883-REDC) (VA, DZ, JC, JMG) and (RED2018-102518-T) (VA, JMG), as well as the CULM Project (HAR2016-77672-P) (DZ, JC); from the Catalan Government - AGAUR through 2017 SGR 212 (DZ); from the Junta de Castilla y León – Consejería de Educación through BDNS 425389 (VA, JMG); and from the Research Foundation – Flanders (FWO) through the NASA project (VA, JC, JMG). In addition, this work was partially supported by the European Social Fund, as VA is the recipient of a predoctoral grant from the Department of Education of Junta de Castilla y León. Lastly, the publication fee was partially supported by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Exploring the influence of seasonal uncertainty in project risk management

27th IPMA World CongressFor years, many research studies have focused on programming projects, assuming a deterministic environment and complete task information. However, during the project performance, schedule may be subject to uncertainty which can lead to significant modifications. This fact has led to an increasing scientific literature in the field. In this article we consider the presence of an uncertainty of seasonal type (e.g. meteorological) that affects some of the activities that comprise the project. We discuss how the project risk can be affected by such uncertainty, depending on the start date of the project. By means of Monte Carlo simulation, we compute the statistical distribution functions of project duration at the end of the project. Then, we represent the variability of the project through the so-called Project Risk Baseline. In addition, we examine various sensitivity metrics - Criticality, Cruciality, Schedule Sensitivity Index -. We use them to prioritize each one of the activities of the project depending on its start date. In the last part of the study we demonstrate the relative importance of project tasks must consider a combined version of these three sensitivity measures.the project SPPORT: “Computational Models for Strategic Project Portfolio Management”, supported by the Regional Government of Castile and Leon (Spain) with grant VA056A12-

Beyond earned value management: a graphical framework for integrated cost, schedule and risk monitoring

26th IPMA World Congress. 2012, Crete, Greece,In this paper, we propose an innovative and simple graphical framework for project control and monitoring, to integrate the dimensions of project cost and schedule with risk management, therefore extending the Earned Value methodology (EVM). EVM allows Project managers to know whether the project has overruns (over-costs and/or delays), but project managers do not know when deviations from planned values are so important that corrective actions should be taken or, in case of good performance, sources of improvement can be detected. From the concept of project planned variability, we build a graphical methodology to know when a project remains “out of control” or “within expected variability” during the project lifecycle. To this aim, we define and represent new control indexes and new cumulative buffers. Five areas in the chart represent five different possible project states. To implement this framework, project managers only need the data provided by EVM traditional analysis and Monte-Carlo simulation. We also explore the sensitivity of the methodology to control variables.Project “Computational Models for Strategic Project Portfolio Management”, supported by the Regional Government of Castile and Leon (Spain) with grant VA056A12-2

Evolution of equity norms in small-world networks

The topology of interactions has been proved very influential in the results of models based on learning and evolutionary game theory. This paper is aimed at investigating the effect of structures ranging from regular ring lattices to random networks, including small-world networks, in a model focused on property distribution norms. The model considers a fixed and finite population of agents who play the Nash bargaining game repeatedly. Our results show that regular networks promote the emergence of the equity norm, while less-structured networks make possible the appearance of fractious regimes. Additionally, our analysis reveals that the speed of adoption can also be affected by the network structureSpanish MICINN Projects CSD2010-00034 SimulPast CONSOLIDER-INGENIO 2010 , TIN2008-06464-C03-02 and DPI2010-16920, and by the Junta de Castilla y León, References BU034A08 and GREX251-200

Economía artificial: métodos de inspiración social en la resolución de problemas complejos

La dimensión social de la Economía le confiere una complejidad que es muy difícil de formalizar en un conjunto de ecuaciones algebraicas. La aproximación de la Economía Experimental (EE) y la de su extensión de la Economía Artificial (EA) con modelos basados en agentes artificiales (ABM), permiten recoger parte de esa complejidad cuando el intercambio es impersonal. En este artículo analizamos desde la EA el paradigmático ejemplo de la subasta doble continua (CDA) y su dinámica social con diferentes tipos de agentes. Los resultados obtenidos con sociedades artificiales, no sólo son relevantes para explicar los mecanismos de la institución, sino que el propio mercado puede ser un vehículo para resolver problemas de gestión de la empresa y de elección y escasez de complejidad nphard. Para ilustrarlo empleamos un ejemplo basado en la aplicación de subastas combinatorias: mediante la programación basada en mercados se puede realizar la asignación de slots de recursos en problemas de gestión de carteras de proyectosMinisterio de Ciencia e Innovación con referencia CSD2010-00034 (SimulPast CONSOLIDER- INGENIO 2010) y el proyecto Application of Agent-Based Computational Economics to Strategic Slot Allocation cofinanciado por EUROCONTROL- SESAR Joint Undertaking (SJU) y la Unión Europea como parte del programa SESA

Asking the Oracle: introducing forecasting principles into agent-based modelling

This paper presents a set of guidelines, imported from the field of forecasting, that can help social simulation and, more specifically, agent-based modelling practitioners to improve the predictive performance and the robustness of their models. The presentation starts with a discussion on the current debate on prediction in social processes, followed by an overview of the recent experience and lessons learnt from the field of forecasting. This is the basis to define standard practices when developing agent-based models under the perspective of forecasting experimentation. In this context, the guidelines are structured in six categories that correspond to key issues that should be taken into account when building a predictor agent-based model: the modelling process, the data adequacy, the space of solutions, the expert involvement, the validation, and the dissemination and replication. The application of these guidelines is illustrated with an existing agent-based model. We conclude by tackling some intrinsic difficulties that agent-based modelling often faces when dealing with prediction models.project Social Ambient Assisting Living - Methods (SociAAL), supported by Spanish Council for Science and Innovation, with grant TIN2011-28335-C02-01 and the Spanish MICINN project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010). We also thank the support from the Programa de Creación y Consolidación de Grupos de Investigación UCM-BSCH, GR35/10-A (921354