Modelli neurali costruttivi di tipo Reservoir Computing per domini strutturati

Il presente lavoro di tesi introduce e discute nuovi modelli di Reti Neurali Ricorsive per l'apprendimento supervisionato di trasduzioni su grafi. Due sono i maggiori contributi apportati: l'adozione di un approccio costruttivo, e l'introduzione di un meccanismo stabile di output-feedback, entrambi innovativi nell'ambito del Reservoir Computing a cui si rifanno i modelli considerati. La combinazione di una strategia costruttiva e dell'utilizzo di modelli di Reservoir Computing ha inoltre permesso la realizzazione di modelli molto efficienti dal punto di vista computazionale. I modelli e le strategie individuate si configurano come uno strumento utile e flessibile nel trattamento di domini complessi attraverso tecniche di Machine Learning, e propongono soluzioni ad alcuni dei problemi aperti nell'ambito del Reservoir Computing. L'analisi sperimentale svolta riguarda l'apprendimento di trasduzioni strutturali da dataset reali appartenenti all'ambito della Chemioinformatica

Reservoir Computing for Learning in Structured Domains

The study of learning models for direct processing complex data structures has gained an increasing interest within the Machine Learning (ML) community during the last decades. In this concern, efficiency, effectiveness and adaptivity of the ML models on large classes of data structures represent challenging and open research issues. The paradigm under consideration is Reservoir Computing (RC), a novel and extremely efficient methodology for modeling Recurrent Neural Networks (RNN) for adaptive sequence processing. RC comprises a number of different neural models, among which the Echo State Network (ESN) probably represents the most popular, used and studied one. Another research area of interest is represented by Recursive Neural Networks (RecNNs), constituting a class of neural network models recently proposed for dealing with hierarchical data structures directly. In this thesis the RC paradigm is investigated and suitably generalized in order to approach the problems arising from learning in structured domains. The research studies described in this thesis cover classes of data structures characterized by increasing complexity, from sequences, to trees and graphs structures. Accordingly, the research focus goes progressively from the analysis of standard ESNs for sequence processing, to the development of new models for trees and graphs structured domains. The analysis of ESNs for sequence processing addresses the interesting problem of identifying and characterizing the relevant factors which influence the reservoir dynamics and the ESN performance. Promising applications of ESNs in the emerging field of Ambient Assisted Living are also presented and discussed. Moving towards highly structured data representations, the ESN model is extended to deal with complex structures directly, resulting in the proposed TreeESN, which is suitable for domains comprising hierarchical structures, and Graph-ESN, which generalizes the approach to a large class of cyclic/acyclic directed/undirected labeled graphs. TreeESNs and GraphESNs represent both novel RC models for structured data and extremely efficient approaches for modeling RecNNs, eventually contributing to the definition of an RC framework for learning in structured domains. The problem of adaptively exploiting the state space in GraphESNs is also investigated, with specific regard to tasks in which input graphs are required to be mapped into flat vectorial outputs, resulting in the GraphESN-wnn and GraphESN-NG models. As a further point, the generalization performance of the proposed models is evaluated considering both artificial and complex real-world tasks from different application domains, including Chemistry, Toxicology and Document Processing

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Climate research Netherlands : research highlights

In the Netherlands the temperature has risen, on average, by 1.6°C since 1900. Regional climate scenarios for the 21st century developed by the Dutch Royal Meteorological Institute [1] show that temperature in the Netherlands will continue to rise and mild winters and hot summers will become more common. On average winters will become wetter and extreme precipitation amounts will increase. The intensity of extreme rain showers in summer will increase and the sea level will continue to rise. Changing climate will affect all segments and sectors of the society and the economy of the Netherlands, but it also brings new opportunities for major innovation

Economics and the Complexity Vision: Chimerical Partners or Elysian Adventurers?

This work began as a review article of: "Complexity and the History of Economic Thought", edited by David Colander, Routledge, London,UK, 2000; & "The Complexity Vision and the Teaching of Economics", edited by David Colander, Edward Elgar, Cheltenham, UK, 2000. It has, in the writing, developed into my own vision of complexity economics

Object-orientation and integration for modelling water resource systems using the ACRU model.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Water is a limiting resource in South Africa, with demand in many catchments exceeding supply, necessitating transfers of water between catchments. This situation requires detailed and integrated management of the country’s water resources, considering environmental, social and economic aspects as outlined in the National Water Act (Act 36 of 1998). Integrated water resources management (IWRM) will require better data and information through monitoring and integrated water resources modelling. The ACRU hydrological model is an important repository of South African water research and knowledge. In recent years there have been technological advances in computer programming techniques and model integration. The thesis for this study was that the valuable knowledge already existing in the ACRU model could be leveraged to provide a better hydrological model to support IWRM in South Africa by: (i) restructuring the model using object-oriented design and programming techniques, and (ii) implementing a model interface standard. Object-oriented restructuring of the ACRU model resulted in a more flexible model enabling better representation of complex water resource systems. The restructuring also resulted in a more extensible model to facilitate the inclusion of new modules and improved data handling. A new model input structure was developed using Extensible Markup Language (XML) to complement the object-oriented structure of the ACRU model. It was recognised that different models have different purposes and strengths. The OpenMI 2.0 model interface standard was implemented for ACRU, enabling ntegration with other OpenMI 2.0 compliant specialised models representing different domains to provide a more holistic IWRM view of water resource systems. Model integration using OpenMI was demonstrated by linking ACRU to the eWater Source river network model. A case study in the upper uMngeni Catchment in South Africa demonstrated: (i) the benefits of the object-oriented design of the restructured ACRU model, in the context of using ACRU to create modelled catchment-scale water resource accounts, and (ii) the integration of ACRU with another model using OpenMI. The case study also demonstrated that despite the improvements to the ACRU model, the simulations are only as good as the model input data

Workshop on computer applications in water management: proceedings of the 1995 workshop

Compiled and edited by L. Ahuja, J. Leppert, K. Rojas, E. Seely.Also published as: Great Plains Agricultural Council publication, no. 154.Includes bibliographical references.Presented at the Workshop on computer applications in water management: proceedings of the 1995 workshop held on May 23-25, 1995 at Colorado State University in Fort Collins, Colorado

Linking farm economics and hydrology: Model integration for watershed-level irrigation management applied to Chile

As largest user of fresh water, the agricultural sector must resolve conflict of objectives ranging from economic goals of farmers to societal and environmental targets. Research must deliver tools to manage these objectives simultaneously. Single disciplines have resolved numerous problems with disciplinary solutions. However, problems emerging from interactions and feedbacks between disciplines can only be assessed with interdisciplinary tools and managed by institutions that coordinate across departments. Such complex problems are becoming an epochal task for Natural Resource Management (NRM). A number of modeling tools exist for irrigation management at watershed level that quantify biophysical processes and water quality. Simultaneously, agricultural economics developed production planning methods for allocating water resources optimally. However, integrated planning support tools are not available that take into account both domains and their interactions. Within a larger research project, it was the objective of this Ph.D. project to develop and test methods that integrate two complex modelling softwares for irrigation management. The distributed runoff model WaSiM-ETH quantifies water flows and evapotranspiration. The dynamic land use model MP-MAS is a multi-agent system in which farmers use economic reasoning to derive cropping decisions under given environmental conditions. Furthermore, the MP-MAS software contains the bucket model EDIC, which parameterizes the distribution of water from rivers to individual farmers through the canal system. Finally, the MP-MAS software was extended with a crop yield model with complementary irrigation. Model integration is understood as service provided within a research context. This context is defined by the study region, the project setting and by the strategic decisions within the research project - such as the choice of partner institutions and disciplines. Within the Maule River watershed in Chile (Linares Province, Region VII), the project ?Integrating Governance and Modeling? assessed the use of water in agriculture. Empirical research questions as well as modeling software were also part of this research context. Integration requires the conceptual, the technical and the procedural level. Conceptual integration describes processes and interactions between farmers, the canal system as distribution infrastructure and the natural system. It also describes how farmers plan and produce within this environment. Here, scale-dependent processes like irrigation efficiency or access to water by individuals were scrutinized. Technical integration is the implementation of the conceptual system into source code, e.g. by adapting legacy software, and by creating a software layer for hierarchical coupling of all software components. Procedural integration is the calibration, analysis, error eradication and validation of these models within the research context. Calibration and analysis of integrated model components is a step-by-step procedure. For all relevant processes and interactions, empirical data was first compiled and cross-evaluated. Then, standalone model components were calibrated so that interactions were parameterized as boundary conditions that are consistent across all disciplines. Empirical data pinpointed conceptual inconsistencies in the description of interactions, and standalone models were improved together with project partners. Ultimately, model components were coupled in such ways that interactions can be analyzed dynamically at minimum model- and software complexity. The calibration process along transdisciplinary cause-effect-chains resulted in the improvement of disciplinary models and model results. For example, the relevance of access to water beyond legalized water rights became apparent when empirical data and models were combined. Also, the calibration of the EDIC model required consistent use of data from all four disciplines and improved the calibration of the MP-MAS model. For the WaSiM-ETH model, an irrigation module was developed that is consistent across scales and reflects the needs of extension workers. Finally, model integration and coupling is discussed as research process. The process of calibrating a model with four components is not only a technical challenge for modellers and data management, but also a procedural challenge with regards to cooperation beyond disciplinary institutions and cultures. The structure of the integration process should be robust against errors and equally facilitate knowledge transfer between disciplines, iterative calibration across disciplines. Success factors are suggested to reduce transaction cost during the integration process.Als größter Nutzer von Süßwasser steht Bewässerungsmanagement in einem Zielkonflikt zwischen den ökonomischen Zielen von Landwirten und Nachhaltigkeitszielen für Gesellschaft und Umwelt. Zur Handhabung dieses Zielkonflikts werden von praxisnaher Forschung Werkzeuge erwartet. Während einzelne Disziplinen erfolgreich disziplinäre Lösungen für etliche Probleme entwickelten, können komplexere Wechselwirkungen nur durch diziplinenübergreifende Betrachtung verstanden werden. Auch die Umsetzung von komplexen Lösungen durch Institutionen bedarf einer Koordination über Fachbereiche hinweg. Solche komplexeren Probleme der Interaktion und Rückkopplung werden zu einer epochalen Aufgabe für das Management natürlicher Ressourcen. Für Bewässerungsmanagement auf Einzugsbereichsebene stehen Modellierungswerkzeuge zur Verfügung, die biophysikalische Prozesse quantifizieren und Wasserqualität darstellen. Parallel werden agrar-ökonomische Methoden genutzt, um Wasserressourcen optimal einzusetzen. Integrierte Planungssysteme hingegen sind nicht erhältlich, die gleichzeitig beide Aspekte sowie Wechselwirkungen dieser Domänen berücksichtigen. Innerhalb eines Rahmenprojektes war es Ziel dieser Dissertation, eine Methode zu entwickeln und zu testen, mit der zwei komplexe Modellierungsprogramme für das Bewässerungsmanagement integriert werden. Als dynamisches Landnutzungsmodell stellt das Multiagentensystem MP-MAS die Produktionsentscheidungen von Landwirten unter gegebenen Umweltbedingungen dar. Gleichzeitig wird das hydrologisches Standort- und Einzugsgebietsmodell WaSiM-ETH verwendet, um Wasserflüsse zu quantifizieren. Zusätzlich beschreibt das Brückenmodell EDIC vereinfacht die Wasserlieferung von Flüssen zu Farmern, und die MP-MAS Software wurde um ein Pflanzenertragsmodell für komplementäre Bewässerung erweitert. Modellintegration wird als Dienstleistung innerhalb eines Forschungskontextes verstanden. Forschungsgebiet, Projektarchitektur und richtungsweisende Projektentscheidungen (z.B. die Wahl von Partnerinstitutionen und -disziplinen) stellen den Rahmen einer Modellintegration dar und werden im Methodenteil beschrieben. Das Einzugsgebiet des Chilenischen Flusses Maule (Linares Province, Region VII) und die darin stattfindende Bewässerungslandwirtschaft wird durch das Projekt ?Integrating Governance and Modeling? betrachtet. Sowohl empirische Fragestellungen als auch Modelierungssoftware werden durch diesen Forschungskontext festgelegt. Der konzeptionelle Teil der Integration beschreibt Prozesse und Wechselwirkungen zwischen Landwirten, dem Kanalsystem sowie den natürlichen Gegebenheiten. Landwirte planen und wirtschaften innerhalb dieses Rahmens. Skalenabhängige Prozessbeschreibungen wie Bewässererungseffizienz und Zugang zu Wasser werden dabei hinterfragt. Technische Integration beschreibt dann die Implementierung des konzeptionellen Systems in Computermodelle bzw. in die existierende Modellsoftware, sowie die Programmierung einer zusätlichen Softwareebene für die hierarchische Kopplung der Modellkomponenten. Die Kalibrierung und Analyse der integrierten Modellkomponenten erfolgte schrittweise. Zuerst wurden empirische Daten zur Beschreibung aller Prozesse undWechselwirkungen gesammelt und ausgewertet. Dann wurden Einzelmodelle so kalibriert, dass in Einzelmodellen die Wechselwirkungen als Randbedingungen konsistent definiert und parametrisiert sind. Hier deuteten empirische Daten auf Inkonsistenzen der konzeptionellen Systembeschreibung hin, so dass Einzelmodelle mit Projektpartnern verbessert werden mussten. Danach wurden Einzelmodelle so gekoppelt, dass Wechselwirkungen bei minimaler Modell- und Softwarekomplexität dynamisch analysiert werden konnten. Ein Kalibrierungsprozess mit disziplinenübergreifenden Ursache-Wirkungs-Ketten resultierte in Verbesserungen disziplinärer Modelle und Ergebnisse. Die Relevanz von Zugang zu Wasser jenseits des legalen Regelwerks wurde durch die Kombination empirischer Daten und Modelle deutlich. Die Kalibrierung des EDIC Modells konnte nur mit konsistenten Nutzung von Daten aus allen Disziplinen erfolgen. Dies verbesserte die Kalibrierung der MP-MAS Modelkomponente. Für das Modell WaSiM-ETH wurde ein Bewässerungsmodel entwickelt, das skalenkonsistent ist und praktischen Ansprüchen entspricht. Zuletzt wird Modellintegration und -kopplung als ein Forschungsprozess diskutiert. Der Kalibrierungsprozess eines Vier-Komponenten-Modells ist nicht nur eine technische Herausforderung für Modell- und Datenmanagement, sondern auch eine prozedurale für die Zusammenarbeit jenseits disziplinärer Institutionen und Kulturen. Die Struktur des Integrationsprozesses sollte gleichzeitig Wissenstransfer zwischen Disziplinen erleichtern, iterative Kalibrierungs- und rekursive Lernprozesse ermöglichen sowie fehlerfreundlich sein. Abschließend werden Erfolgsfaktoren vorgeschlagen welche Transaktionskosten in Integrationsprozessen reduzieren