A dynamic adaptive framework for improving case-based reasoning system performance

An optimal performance of a Case-Based Reasoning (CBR) system means, the CBR system must be efficient both in time and in size, and must be optimally competent. The efficiency in time is closely related to an efficient and optimal retrieval process over the Case Base of the CBR system. Efficiency in size means that the Case Library (CL) size should be minimal. Therefore, the efficiency in size is closely related to optimal case learning policies, optimal meta-case learning policies, optimal case forgetting policies, etc. On the other hand, the optimal competence of a CBR system means that the number of problems that the CBR system can satisfactorily solve must be maximum. To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dynamic or continuous domain (data stream). In this thesis, a Dynamic Adaptive Case Library framework (DACL) is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the CL to be efficient in size, especially in continuous domains. DACL learns cases and organizes them into dynamic cluster structures. The DACL is able to adapt itself to a dynamic environment, where new clusters, meta-cases or prototype of cases, and associated indexing structures (discriminant trees, k-d trees, etc.) can be formed, updated, or even removed. DACL offers a possible solution to the management of the large amount of data generated in an unsupervised continuous domain (data stream). In addition, we propose the use of a Multiple Case Library (MCL), which is a static version of a DACL, with the same structure but being defined statically to be used in supervised domains. The thesis work proposes some techniques for improving the indexation and the retrieval task. The most important indexing method is the NIAR k-d tree algorithm, which improves the retrieval time and competence, compared against the baseline approach (a flat CL) and against the well-known techniques based on using standard k-d tree strategies. The proposed Partial Matching Exploration (PME) technique explores a hierarchical case library with a tree indexing-structure aiming at not losing the most similar cases to a query case. This technique allows not only exploring the best matching path, but also several alternative partial matching paths to be explored. The results show an improvement in competence and time of retrieving of similar cases. Through the experimentation tests done, with a set of well-known benchmark supervised databases. The dynamic building of prototypes in DACL has been tested in an unsupervised domain (environmental domain) where the air pollution is evaluated. The core task of building prototypes in a DACL is the implementation of a stochastic method for the learning of new cases and management of prototypes. Finally, the whole dynamic framework, integrating all the main proposed approaches of the research work, has been tested in simulated unsupervised domains with several well-known databases in an incremental way, as data streams are processed in real life. The conclusions outlined that from the experimental results, it can be stated that the dynamic adaptive framework proposed (DACL/MCL), jointly with the contributed indexing strategies and exploration techniques, and with the proposed stochastic case learning policies, and meta-case learning policies, improves the performance of standard CBR systems both in supervised domains (MCL) and in unsupervised continuous domains (DACL).El rendimiento óptimo de un sistema de razonamiento basado en casos (CBR) significa que el sistema CBR debe ser eficiente tanto en tiempo como en tamaño, y debe ser competente de manera óptima. La eficiencia temporal está estrechamente relacionada con que el proceso de recuperación sobre la Base de Casos del sistema CBR sea eficiente y óptimo. La eficiencia en tamaño significa que el tamaño de la Base de Casos (CL) debe ser mínimo. Por lo tanto, la eficiencia en tamaño está estrechamente relacionada con las políticas óptimas de aprendizaje de casos y meta-casos, y las políticas óptimas de olvido de casos, etc. Por otro lado, la competencia óptima de un sistema CBR significa que el número de problemas que el sistema puede resolver de forma satisfactoria debe ser máximo. Mejorar u optimizar las tres dimensiones de un sistema CBR al mismo tiempo es un reto difícil, ya que están relacionadas entre sí, y se vuelve aún más difícil cuando se aplica el sistema de CBR a un dominio dinámico o continuo (flujo de datos). En esta tesis se propone el Dynamic Adaptive Case Library framework (DACL) para mejorar el rendimiento del sistema CBR especialmente con la reducción del tiempo de recuperación, aumentando la competencia del sistema CBR, manteniendo y adaptando la CL para ser eficiente en tamaño, especialmente en dominios continuos. DACL aprende casos y los organiza en estructuras dinámicas de clusters. DACL es capaz de adaptarse a entornos dinámicos, donde los nuevos clusters, meta-casos o prototipos de los casos, y las estructuras asociadas de indexación (árboles discriminantes, árboles k-d, etc.) se pueden formar, actualizarse, o incluso ser eliminados. DACL ofrece una posible solución para la gestión de la gran cantidad de datos generados en un dominio continuo no supervisado (flujo de datos). Además, se propone el uso de la Multiple Case Library (MCL), que es una versión estática de una DACL, con la misma estructura pero siendo definida estáticamente para ser utilizada en dominios supervisados. El trabajo de tesis propone algunas técnicas para mejorar los procesos de indexación y de recuperación. El método de indexación más importante es el algoritmo NIAR k-d tree, que mejora el tiempo de recuperación y la competencia, comparado con una CL plana y con las técnicas basadas en el uso de estrategias de árboles k-d estándar. Partial Matching Exploration (PME) technique, la técnica propuesta, explora una base de casos jerárquica con una indexación de estructura de árbol con el objetivo de no perder los casos más similares a un caso de consulta. Esta técnica no sólo permite explorar el mejor camino coincidente, sino también varios caminos parciales alternativos coincidentes. Los resultados, a través de la experimentación realizada con bases de datos supervisadas conocidas, muestran una mejora de la competencia y del tiempo de recuperación de casos similares. Además la construcción dinámica de prototipos en DACL ha sido probada en un dominio no supervisado (dominio ambiental), donde se evalúa la contaminación del aire. La tarea central de la construcción de prototipos en DACL es la implementación de un método estocástico para el aprendizaje de nuevos casos y la gestión de prototipos. Por último, todo el sistema, integrando todos los métodos propuestos en este trabajo de investigación, se ha evaluado en dominios no supervisados simulados con varias bases de datos de una manera gradual, como se procesan los flujos de datos en la vida real. Las conclusiones, a partir de los resultados experimentales, muestran que el sistema de adaptación dinámica propuesto (DACL / MCL), junto con las estrategias de indexación y de exploración, y con las políticas de aprendizaje de casos estocásticos y de meta-casos propuestas, mejora el rendimiento de los sistemas estándar de CBR tanto en dominios supervisados (MCL) como en dominios continuos no supervisados (DACL).Postprint (published version

El conocimiento de los electrones determina la interacción molecular

Página web divulgativa.Peer Reviewe

Environmental data stream mining through a case-based stochastic learning approach

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Environmental data stream mining is an open challenge for Data Science. Common methods used are static because they analyze a static set of data, and provide static data-driven models. Environmental systems are dynamic and generate a continuous data stream. Dynamic methods coping with the temporal nature of data must be provided in Data Science. Our proposal is to model each environmental information unit, timely generated, as a new case/experience in a Case-Based Reasoning (CBR) system. This contribution aims to incrementally build and manage a Dynamic Adaptive Case Library (DACL). In this paper, a stochastic method for the learning of new cases and management of prototypes to create and manage the DACL in an incremental way is introduced. This stochastic method works with two main moments. An evaluation of the method has been carried using a data stream of air quality of the city of Obregon, Sonora. México, with good results. In addition, other datasets have been mined to ensure the generality of the approach.Peer ReviewedPostprint (author's final draft

Dynamic learning of cases from data streams

This paper presents a dynamic adaptive framework for building a case library being able to cope with a data stream in the field of Case-Based Reasoning. The framework provides a three-layer architecture formed by a set of case libraries dynamically built. This Dynamic and Adaptive Case Library (DACL), can process in an incremental way a data stream, and can be used as a classification model or a regression model, depending on the predicted variable. In this paper, the work is focused on classification tasks. Each case library has a first layer formed by the dynamic clusters of cases, a second one formed by the meta-cases or prototypes of the cluster, and a third one formed by an incremental indexing structure. In our approach, some variant of k-d tres have been used, in addition to an exploration technique to get a more efficient retrieval time. This three-layer famework can be constructed in an incremental way. Several meta-case learning approaches are proposed, as well as some case learning strategies. The framework has been tested with several datasets. The experimental results show a very good performance in comparison with a batch learning scheme over the same data.Peer ReviewedPostprint (author's final draft

Asymmetric 1, 3-dipolar cycloaddition reactions between methacrylonitrile and nitrones catalysed by well-defined M(diphosphane) (M=Rh, Ir) complexes

The cationic half-sandwich aqua-complexes (¿ 5-C5Me5)M(PP*)(H2O)]SbF6]2 M=Rh, Ir; PP* =(R)-Benphos, (R)-Cyphos, (2R, 4R)-Norphos] catalyse the 1, 3-dipolar cycloaddition reaction of nitrones with methacrylonitrile with perfect regioselectivity, low-to-perfect endo-selectivity and low-to-moderate enantioselectivity. The active species involved in the catalytic process, (¿ 5-C5Me5)M(PP*)(methacrylonitrile)]SbF6]2, have been isolated and characterised as mixtures of the (S)- and (R)-at-metal epimers. NMR measurements of these mixtures indicated that the (R M)-isomers epimerise to the corresponding (S M) counterparts. The molecular structure of the rhodium complex (S Rh, R C)-(¿ 5-C5Me5)Rh((R)-Benphos)(methacrylonitrile)]SbF6]2 has been determined by X-ray diffraction methods. Diastereomerically pure (S Rh, R C)-(¿ 5-C5Me5)Rh(PP*)(methacrylonitrile)]SbF6]2 compounds catalyse stoichiometrically the above mentioned dipolar cycloaddition reaction with up to 90% enantiomeric excess, thus indicating the influence of the metal handedness on the catalytic stereochemical outcome. Catalysts can be recycled up to three times without a significant loss of either activity or selectivity

Synthesis and catalytic activity of well-defined Co(i) complexes based on NHC–phosphane pincer ligands

A new methodology for the preparation of Co(I)–NHC (NHC = N-heterocyclic carbene) complexes, namely, [Co(PCNHCP)(CO)2][Co(CO)4] (1) and [Co(PCNHCP)(CO)2]BF4 (2), has been developed (PCNHCP = 1,3-bis(2-(diphenylphosphanyl)ethyl)-imidazol-2-ylidene). Both complexes can be straightforwardly prepared by direct reaction of their parent imidazolium salts with the Co(0) complex Co2(CO)8. Complex 1 efficiently catalyses the reductive amination of furfural and levulinic acid employing silanes as reducing agents under mild conditions. Furfural has been converted into a variety of secondary and tertiary amines employing dimethyl carbonate as the solvent, while levulinic acid has been converted into pyrrolidines under solventless conditions. Dehydrocoupling of the silane to give polysilanes has been observed to occur as a side reaction of the hydrosilylation process

An approach for an architecture to embodied procedural reasoning

Some research in intelligent manufacturing systems summarizes the importance of developing new methods and techniques that should be more knowledge intensive, applied at the level of embedded devices. To bring a solution for this demand we propose an embedded architecture for micro-controllers based on the hypothesis is it possible to introduce intelligence in microcontrollers by applying some solutions from the area of Multiagent Systems and in particular Belief-Desires-Intentions (BDI) agents to model intelligent computational units that are physically embedded in the world. This approach was first formulated by Deepak Kumar and it is adopted as the basis of our research. This research is focused in the development of a BDI architecture which could provide flexible reasoning capabilities wich can cope with complicated tasks executed by an embodied system. The intelligent part is based in procedural reasoning -Belief, Desires and Intentions- (BDI).Postprint (published version

Bioinformatics: a promising field for case-based reasoning

Case Based Reasoning has been applied in different fields such as medicine, industry, tutoring systems and others, but in the CBR there are many areas to explore. Nowadays, some research works in Bioinformatics are attempting to use CBR like a tool for classifying DNA genes. Specially the microarrays have been applied increasingly to improve medical decision-making, and to the diagnosis of different diseases like cancer. This research work analyzes the Microarrays structure, and the initial concepts to understand how DNA structure is studied in the Bioinformatics' field. In last years the CBR has been related to Bioinformatics and Microarrays. In this report, our interest is to find out how the Microarrays technique could help in the CBR field, and specially in the Case-Based Maintenance policies.Postprint (published version

Case base maintenance: terms and directions

Since last years Case Base Reasoning (CBR) field has been growing, and Case Base Maintenance (CBM) is getting more important. Recent research has focused on case-base maintenance, addressing such issues as maintaining consistency, preserving competence, and controlling case-base grow. A set of dimensions for case-base maintenance proposed by Leake and Wilson, provides a framework for understanding and expanding CBM research. Taking this contribution into account, the aims of our work is to do a framework where the basics concepts of CBM are explained, and even more, as second objective we do a brief resume of some relevant contributions made by the scientific CBR community. Starting where Wilson and Leake research work ends.Postprint (published version

Dinuclear pyridine-4-thiolate-bridged rhodium and iridium complexes as ditopic building blocks in molecular architecture

A series of dinuclear pyridine-4-thiolate (4-Spy)-bridged rhodium and iridium compounds [M(μ-4-Spy)(diolef)]2 [diolef = 1,5-cyclooctadiene (cod), M = Rh (1), Ir (2); diolef = 2,5-norbornadiene (nbd), M = Rh (3)] were prepared by the reaction of Li(4-Spy) with the appropriate compound [M(μ-Cl)(diolef)]2 (M = Rh, Ir). The dinuclear compound [Rh(μ-4-Spy)(CO)(PPh3)]2 (4) was obtained by the reaction of [Rh(acac)(CO)(PPh3)] (acac = acetylacetonate) with 4-pySH. Compounds 1-4 were assessed as metalloligands in self-assembly reactions with the cis-blocked acceptors [M(cod)(NCCH3)2](BF 4) [M = Rh (a), Ir (b)] and [M(H2O)2(dppp)] (OTf)2 [M = Pd (c), Pt (d); dppp = 1,3-bis(diphenylphosphino)propane] . The homometallic hexanuclear metallomacrocycles [{M2(μ-4-Spy) 2(cod)2}2{M(cod)}2](BF 4)2 (M = Rh [(1a)2], Ir [(2b)2]) and the heterometallic hexanuclear metallomacrocycles [{Rh2(μ-4-Spy) 2(cod)2}2{Ir(cod)}2](BF 4)2 [(1b)2], [{Rh2(μ-4-Spy) 2(cod)2}2{M′(dppp)}2](OTf) 4 (M′ = Pd [(1c)2], Pt [(1d)2]), and [{Ir2(μ-4-Spy)2(cod)2}2{M′ (dppp)}2](OTf)4 (M′ = Pd [(2c)2], Pt [(2d)2]) were obtained. NMR spectroscopy in combination with electrospray ionization mass spectrometry was used to elucidate the nature of the metalloligands and their respective supramolecular assemblies. Most of the synthesized species were found to be nonrigid in solution, and their fluxional behavior was studied by variable-temperature 1H NMR spectroscopy. An X-ray diffraction study of the assemblies (1a)2 and (1d)2 revealed the formation of rectangular (9.6 Å × 6.6 Å) hexanuclear metallomacrocycles with alternating dinuclear (Rh2) and mononuclear (Rh or Pt) corners. The hexanuclear core is supported by four pyridine-4-thiolate linkers, which are bonded through the thiolate moieties to the dinuclear rhodium units, exhibiting a bent-anti arrangement, and through the peripheral pyridinic nitrogen atoms to the mononuclear corners.Financial support for this work was provided by the Ministerio de Economía y Competitividad (MINECO/FEDER) of Spain (Projects CTQ2010-15221 and CTQ2012-31335), Diputación General de Aragón (Group E07), and Fondo Social Europeo.Peer Reviewe