Automatic synthesis of fuzzy systems: An evolutionary overview with a genetic programming perspective

Studies in Evolutionary Fuzzy Systems (EFSs) began in the 90s and have experienced a fast development since then, with applications to areas such as pattern recognition, curve‐fitting and regression, forecasting and control. An EFS results from the combination of a Fuzzy Inference System (FIS) with an Evolutionary Algorithm (EA). This relationship can be established for multiple purposes: fine‐tuning of FIS's parameters, selection of fuzzy rules, learning a rule base or membership functions from scratch, and so forth. Each facet of this relationship creates a strand in the literature, as membership function fine‐tuning, fuzzy rule‐based learning, and so forth and the purpose here is to outline some of what has been done in each aspect. Special focus is given to Genetic Programming‐based EFSs by providing a taxonomy of the main architectures available, as well as by pointing out the gaps that still prevail in the literature. The concluding remarks address some further topics of current research and trends, such as interpretability analysis, multiobjective optimization, and synthesis of a FIS through Evolving methods

The Malleable Politics of Activation Reform: the ‘Hartz’ Reforms in Comparative Perspective

In this paper we compare the Hartz reforms in Germany with three other major labor market activation reforms carried out by center-left governments. Two of the cases, Britain and Germany, involved radically neoliberal “mandatory” activation policies, whereas in the Netherlands and Ireland radical activation change took a very different “enabling” form. Two of the cases, Ireland and Germany, were path deviant, Britain and the Netherlands were path dependent. We explain why Germany underwent “mandatory” and path deviant activation by focusing on two features of the policy discourse. First, the coordinative (or elite level) discourse was “ensilaged” sealing policy formation off from dissenting actors and, until belatedly unwrapped for enactment, from the wider communicative (legitimating) discourse. This is what the British and German cases had in common and the result was reform that viewed long term unemployment as personal failure rather than market failure. Second, although the German policy-making system lacked the “authoritative” features that facilitated reform in the British case, and the Irish policymaking system lacked the “reflexive” mechanisms that facilitated reform in the Dutch case, in both Germany and Ireland the communicative discourses were reshaped by novel institutional vehicles (the Hartz Commission in the German case, FÁS in the Irish case) that served to fundamentally alter systemconstitutive perceptions about policy. In the Irish and German cases “government by commission” created a realignment of advocacy coalitions with one coalition acquiring a new, ideologically-dominant and path deviating narrative. The findings suggest that major reform of labor market and welfare state policy may be much more malleable than previously thought

Proceedings of the Workshop Semantic Content Acquisition and Representation (SCAR) 2007

This is the proceedings of the Workshop on Semantic Content Acquisition and Representation, held in conjunction with NODALIDA 2007, on May 24 2007 in Tartu, Estonia.</p

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

The Malleable Politics of Welfare-to-Work Reform: Germany's "Hartz" activation compared with Dutch, British and Irish cases. ACES Cases No. 2009.1

We compare the Hartz reforms in Germany with three other major labor market activation reforms carried out by center-left governments. Britain and Germany developed radically neoliberal “mandatory” activation policies, whereas in the Netherlands and Ireland radical activation change took a very different “enabling” form. The Irish and German cases were path deviant, the British and Dutch path dependent. We explain why Germany underwent “mandatory” and path deviant activation by focusing on two features of the policy discourse. First, the elite level discourse was “ensilaged” sealing policy formation off from dissenting actors. This is what the British and German cases had in common and the result was reform that identified long term unemployment as social delinquency rather than market failure. Second, although the German policy-making system lacked the “authoritative” features that facilitated reform in the British case, and the Irish policy-making system lacked the “reflexive” mechanisms that facilitated reform in the Dutch case, in both Germany and Ireland the wider legitimating discourses were reshaped by novel institutional vehicles (the Hartz Commission and FÁS) that served to fundamentally alter system-constitutive perceptions about policy. The findings suggest that major reform of welfare-to-work policy may be much more malleable than previously thought

From Frequency to Meaning: Vector Space Models of Semantics

Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term-document, word-context, and pair-pattern matrices, yielding three classes of applications. We survey a broad range of applications in these three categories and we take a detailed look at a specific open source project in each category. Our goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs for those who are already familiar with the area, and to provide pointers into the literature for those who are less familiar with the field