Intelligence by Design: Principles of Modularity and Coordination for Engineerin

All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dissertation describes an approach, Behavior-Oriented Design (BOD) for engineering complex agents. A complex agent is one that must arbitrate between potentially conflicting goals or behaviors. Behavior-oriented design builds on work in behavior-based and hybrid architectures for agents, and the object oriented approach to software engineering. The primary contributions of this dissertation are: 1.The BOD architecture: a modular architecture with each module providing specialized representations to facilitate learning. This includes one pre-specified module and representation for action selection or behavior arbitration. The specialized representation underlying BOD action selection is Parallel-rooted, Ordered, Slip-stack Hierarchical (POSH) reactive plans. 2.The BOD development process: an iterative process that alternately scales the agent's capabilities then optimizes the agent for simplicity, exploiting tradeoffs between the component representations. This ongoing process for controlling complexity not only provides bias for the behaving agent, but also facilitates its maintenance and extendibility. The secondary contributions of this dissertation include two implementations of POSH action selection, a procedure for identifying useful idioms in agent architectures and using them to distribute knowledge across agent paradigms, several examples of applying BOD idioms to established architectures, an analysis and comparison of the attributes and design trends of a large number of agent architectures, a comparison of biological (particularly mammalian) intelligence to artificial agent architectures, a novel model of primate transitive inference, and many other examples of BOD agents and BOD development.

Building Grounded Abstractions for Artificial Intelligence Programming

Most Artificial Intelligence (AI) work can be characterized as either ``high-level'' (e.g., logical, symbolic) or ``low-level'' (e.g., connectionist networks, behavior-based robotics). Each approach suffers from particular drawbacks. High-level AI uses abstractions that often have no relation to the way real, biological brains work. Low-level AI, on the other hand, tends to lack the powerful abstractions that are needed to express complex structures and relationships. I have tried to combine the best features of both approaches, by building a set of programming abstractions defined in terms of simple, biologically plausible components. At the ``ground level'', I define a primitive, perceptron-like computational unit. I then show how more abstract computational units may be implemented in terms of the primitive units, and show the utility of the abstract units in sample networks. The new units make it possible to build networks using concepts such as long-term memories, short-term memories, and frames. As a demonstration of these abstractions, I have implemented a simulator for ``creatures'' controlled by a network of abstract units. The creatures exist in a simple 2D world, and exhibit behaviors such as catching mobile prey and sorting colored blocks into matching boxes. This program demonstrates that it is possible to build systems that can interact effectively with a dynamic physical environment, yet use symbolic representations to control aspects of their behavior.

Electrical Design: A Problem for Artificial Intelligence Research

This report outlines the problem of intelligent failure recovery in a problem-solver for electrical design. We want our problem solver to learn as much as it can from its mistakes. Thus we cast the engineering design process on terms of Problem Solving by Debugging Almost-Right Plans, a paradigm for automatic problem solving based on the belief that creation and removal of "bugs" is an unavoidable part of the process of solving a complex problem. The process of localization and removal of bugs called for by the PSBDARP theory requires an approach to engineering analysis in which every result has a justification which describes the exact set of assumptions it depends upon. We have developed a program based on Analysis by Propagation of Constraints which can explain the basis of its deductions. In addition to being useful to a PSBDARP designer, these justifications are used in Dependency-Directed Backtracking to limit the combinatorial search in the analysis routines. Although the research we will describe is explicitly about electrical circuits, we believe that similar principles and methods are employed by other kinds of engineers, including computer programmers.

Sistema d'anàlisi financer: tresoreria amb eines Business Intelligence

El projecte tracte d' implementar una solució de Business Intelligence sota la plataforma Microsoft.Aquest projecte va destinat al Departament de Comptabilitat de l' Ajuntament de Cambrils, i està relacionat amb la funció del control de les despeses i els ingressos

Psychometric properties of the Spanish version of the Collective Efficacy Questionnaire for Sports

Resumen tomado de la publicaci??n

Psychometric properties of the Spanish version of the Work Group Emotional Intelligence Profi le-Short version

Resumen tomado de la publicaci??n

Spanish adaptation of the Adolescents' Perceived Collective Family Efficacy Scale

Resumen tomado de la publicaci??n

Short-term storage and mental speed account for the relationship between working memory and fluid intelligence. 'El almacenamiento a corto plazo y la velocidad mental dan cuenta de la relaci??n entre memoria de trabajo e inteligencia fluida'

Resumen tomado de la publicaci??n

Neuroticism, intelligence, and intra-individual variability in elementary cognitive tasks : Testing the mental noise hypothesis. 'Neuroticismo, inteligencia y variabilidad intra-individual en tareas cognitivas elementales : contraste de la hip??tesis del ruido neuronal'

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Does the collective strategy ensure the small and medium sized perdurability?

El posicionamiento estratégico se define como el punto de partida de toda reflexión de la organización (por más pequeña que sea) que pretende poner un lugar dentro de la empresa el”give back” del propio rendimiento. En el caso de la estrategia colectiva, no sólo hay una visión de un dirigente (manager), al contrario hay una gran cantidad de visiones de diferentes gestores, que tendrá que tomar decisiones comunes beneficiosas para sus propios intereses y el común de los intereses de cada empresa. Por lo tanto, es esencial que la situación actual y los objetivos a alcanzar estén claramente definidos desde el comienzo de la elaboración de la estrategia, para evitar las posibles divergencias que puedan poner en riesgo la coherencia de la estrategia. Con los problemas encontrados en la PYME francesa, como el inicio de la actividad, los problemas financieros, la integración organizativa y la competencia y el desarrollo de productos, la estrategia colectiva aparece como una posible solución que permite a la PYME perdurar en el tiempo. En Francia, impulsada por el Gobierno y otras instituciones financieras y administrativas, esta estrategia ha conseguido resultados que antes no se habían pensado, como lo demuestra el estudio de modelo urbano el cuál es presentado en esta investigación. Esta es la razón y el por qué se eligió este tema.

Assessment of the global intelligence and selective cognitive capacities in preterm 8-year-old children

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Adaptive business intelligence for an open negotiation environment

Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

Six Degrees: The New Science of Networks (Collective Dynamics Group ISERP -- Columbia University) Course Syllabus

Six Degrees: The New Science of Networks (Sociology, W3233, Spring 2006) Original URL: http://cdg.columbia.edu/cdg/courses/spring06/sixDegrees/syllabus.jsp

W3233 -- Networks and Complexity in Social Systems (Collective Dynamics Group ISERP -- Columbia University) Course Syllabus

The Networks and Complexity in Social Systems course commences with an overview of the nascent field of complex networks, dividing it into three related but distinct strands: Statistical description of large scale networks, viewed as static objects; the dynamic evolution of networks, where now the structure of the network is understood in terms of a growth process; and dynamical processes that take place on fixed networks; that is, "networked dynamical systems". (A fourth area of potential research ties all the previous three strands together under the rubric of co-evolution of networks and dynamics, but very little research has been done in this vein and so it is omitted.) The remainder of the course treats each of the three strands in greater detail, introducing technical knowledge as required, summarizing the research papers that have introduced the principal ideas, and pointing out directions for future development. With regard to networked dynamical systems, the course treats in detail the more specific topic of information propagation in networks, in part because this topic is of great relevance to social science, and in part because it has received the most attention in the literature to date.

Artificial Intelligence

Pearon's resource from the Brookshear Chapter