Inovações tecnológicas e a complexidade do sistema econômico

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Finanças comportamentais e modelos baseados em agentes

Pós-graduação em Economia - FCLAR

Specification, execution and verification of interaction protocols: an approach based on computational logic

Interaction protocols establish how different computational entities can interact with each other. The interaction can be finalized to the exchange of data, as in 'communication protocols', or can be oriented to achieve some result, as in 'application protocols'. Moreover, with the increasing complexity of modern distributed systems, protocols are used also to control such a complexity, and to ensure that the system as a whole evolves with certain features. However, the extensive use of protocols has raised some issues, from the language for specifying them to the several verification aspects. Computational Logic provides models, languages and tools that can be effectively adopted to address such issues: its declarative nature can be exploited for a protocol specification language, while its operational counterpart can be used to reason upon such specifications. In this thesis we propose a proof-theoretic framework, called SCIFF, together with its extensions. SCIFF is based on Abductive Logic Programming, and provides a formal specification language with a clear declarative semantics (based on abduction). The operational counterpart is given by a proof procedure, that allows to reason upon the specifications and to test the conformance of given interactions w.r.t. a defined protocol. Moreover, by suitably adapting the SCIFF Framework, we propose solutions for addressing (1) the protocol properties verification (g-SCIFF Framework), and (2) the a-priori conformance verification of peers w.r.t. the given protocol (AlLoWS Framework). We introduce also an agent based architecture, the SCIFF Agent Platform, where the same protocol specification can be used to program and to ease the implementation task of the interacting peers.

Argumentation and artifacts for intelligent multi-agent systems

Reasoning under uncertainty is a human capacity that in software system is necessary and often hidden. Argumentation theory and logic make explicit non-monotonic information in order to enable automatic forms of reasoning under uncertainty. In human organization Distributed Cognition and Activity Theory explain how artifacts are fundamental in all cognitive process. Then, in this thesis we search to understand the use of cognitive artifacts in an new argumentation framework for an agent-based artificial society.

Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.

A Semantic-based Framework for Digital Survey of Architectural Heritage

The research aims at developing a framework for semantic-based digital survey of architectural heritage. Rooted in knowledge-based modeling which extracts mathematical constraints of geometry from architectural treatises, as-built information of architecture obtained from image-based modeling is integrated with the ideal model in BIM platform. The knowledge-based modeling transforms the geometry and parametric relation of architectural components from 2D printings to 3D digital models, and create large amount variations based on shape grammar in real time thanks to parametric modeling. It also provides prior knowledge for semantically segmenting unorganized survey data. The emergence of SfM (Structure from Motion) provides access to reconstruct large complex architectural scenes with high flexibility, low cost and full automation, but low reliability of metric accuracy. We solve this problem by combing photogrammetric approaches which consists of camera configuration, image enhancement, and bundle adjustment, etc. Experiments show the accuracy of image-based modeling following our workflow is comparable to that from range-based modeling. We also demonstrate positive results of our optimized approach in digital reconstruction of portico where low-texture-vault and dramatical transition of illumination bring huge difficulties in the workflow without optimization. Once the as-built model is obtained, it is integrated with the ideal model in BIM platform which allows multiple data enrichment. In spite of its promising prospect in AEC industry, BIM is developed with limited consideration of reverse-engineering from survey data. Besides representing the architectural heritage in parallel ways (ideal model and as-built model) and comparing their difference, we concern how to create as-built model in BIM software which is still an open area to be addressed. The research is supposed to be fundamental for research of architectural history, documentation and conservation of architectural heritage, and renovation of existing buildings.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Computational simulations of latent heat thermal energy storage systems - with innovative and first-principles based simulation for the underlying unsteady melting (and solidification) processes

This thesis develops an effective modeling and simulation procedure for a specific thermal energy storage system commonly used and recommended for various applications (such as an auxiliary energy storage system for solar heating based Rankine cycle power plant). This thermal energy storage system transfers heat from a hot fluid (termed as heat transfer fluid - HTF) flowing in a tube to the surrounding phase change material (PCM). Through unsteady melting or freezing process, the PCM absorbs or releases thermal energy in the form of latent heat. Both scientific and engineering information is obtained by the proposed first-principle based modeling and simulation procedure. On the scientific side, the approach accurately tracks the moving melt-front (modeled as a sharp liquid-solid interface) and provides all necessary information about the time-varying heat-flow rates, temperature profiles, stored thermal energy, etc. On the engineering side, the proposed approach is unique in its ability to accurately solve – both individually and collectively – all the conjugate unsteady heat transfer problems for each of the components of the thermal storage system. This yields critical system level information on the various time-varying effectiveness and efficiency parameters for the thermal storage system.

Energy and conductance state modeling of power electronic converters for DC microgrids

This document will demonstrate the methodology used to create an energy and conductance based model for power electronic converters. The work is intended to be a replacement for voltage and current based models which have limited applicability to the network nodal equations. Using conductance-based modeling allows direct application of load differential equations to the bus admittance matrix (Y-bus) with a unified approach. When applied directly to the Y-bus, the system becomes much easier to simulate since the state variables do not need to be transformed. The proposed transformation applies to loads, sources, and energy storage systems and is useful for DC microgrids. Transformed state models of a complete microgrid are compared to experimental results and show the models accurately reflect the system dynamic behavior.

Performance Availability and Anticipatory Change Planning of Intralogistics Systems: A Simulation-Based Approach

In recent years, the ability to respond to real time changes in operations and reconfigurability in equipment are likely to become essential characteristics for next generation intralogistics systems as well as the level of automation, cost effectiveness and maximum throughput. In order to cope with turbulences and the increasing level of dynamic conditions, future intralogistics systems have to feature short reaction times, high flexibility in processes and the ability to adapt to frequent changes. The increasing autonomy and complexity in processes of today’s intralogistics systems requires new and innovative management approaches, which allow a fast response to (un)anticipated events and adaptation to changing environment in order to reduce the negative consequences of these events. The ability of a system to respond effectively a disruption depends more on the decisions taken before the event than those taken during or after. In this context, anticipatory change planning can be a usable approach for managers to make contingency plans for intralogistics systems to deal with the rapidly changing marketplace. This paper proposes a simulation-based decision making framework for the anticipatory change planning of intralogistics systems. This approach includes the quantitative assessments based on the simulation in defined scenarios as well as the analysis of performance availability that combines the flexibility corridors of different performance dimensions. The implementation of the approach is illustrated on a new intralogistics technology called the Cellular Transport System.

Computer Simulation of Crowd Dynamics and Destructive Crowd Behavior

The social processes that lead to destructive behavior in celebratory crowds can be studied through an agent-based computer simulation. Riots are an increasingly common outcome of sports celebrations, and pose the potential for harm to participants, bystanders, property, and the reputation of the groups with whom participants are associated. Rioting cannot necessarily be attributed to the negative emotions of individuals, such as anger, rage, frustration and despair. For instance, the celebratory behavior (e.g., chanting, cheering, singing) during UConn’s “Spring Weekend” and after the 2004 NCAA Championships resulted in several small fires and overturned cars. Further, not every individual in the area of a riot engages in violence, and those who do, do not do so continuously. Instead, small groups carry out the majority of violent acts in relatively short-lived episodes. Agent-based computer simulations are an ideal method for modeling complex group-level social phenomena, such as celebratory gatherings and riots, which emerge from the interaction of relatively “simple” individuals. By making simple assumptions about individuals’ decision-making and behaviors and allowing actors to affect one another, behavioral patterns emerge that cannot be predicted by the characteristics of individuals. The computer simulation developed here models celebratory riot behavior by repeatedly evaluating a single algorithm for each individual, the inputs of which are affected by the characteristics of nearby actors. Specifically, the simulation assumes that (a) actors possess 1 of 5 distinct social identities (group memberships), (b) actors will congregate with actors who possess the same identity, (c) the degree of social cohesion generated in the social context determines the stability of relationships within groups, and (d) actors’ level of aggression is affected by the aggression of other group members. Not only does this simulation provide a systematic investigation of the effects of the initial distribution of aggression, social identification, and cohesiveness on riot outcomes, but also an analytic tool others may use to investigate, visualize and predict how various individual characteristics affect emergent crowd behavior.

Network-based biomarkers in Alzheimer's disease: review and future directions

By 2050 it is estimated that the number of worldwide Alzheimer?s disease (AD) patients will quadruple from the current number of 36 million people. To date, no single test, prior to postmortem examination, can confirm that a person suffers from AD. Therefore, there is a strong need for accurate and sensitive tools for the early diagnoses of AD. The complex etiology and multiple pathogenesis of AD call for a system-level understanding of the currently available biomarkers and the study of new biomarkers via network-based modeling of heterogeneous data types. In this review, we summarize recent research on the study of AD as a connectivity syndrome. We argue that a network-based approach in biomarker discovery will provide key insights to fully understand the network degeneration hypothesis (disease starts in specific network areas and progressively spreads to connected areas of the initial loci-networks) with a potential impact for early diagnosis and disease-modifying treatments. We introduce a new framework for the quantitative study of biomarkers that can help shorten the transition between academic research and clinical diagnosis in AD.

Development of the infrastructure for a multi-agent traffic management system simulation

This document contains detailed description of the design and the implementation of a multi-agent application controlling traffic lights in a city together with a system for simulating traffic and testing. The goal of this thesis is to design and build a simplified intelligent and distributed solution to the problem with the traffic in the big cities following different good practices in order to allow future refining of the model of the real world. The problem of the traffic in the big cities is still a problem that cannot be solved. Not only is the increasing number of cars a reason for the traffic jams, but also the way the traffic is organized. Usually, the intersections with traffic lights are replaced by roundabouts or interchanges to increase the number of cars that can cross the intersection in certain time. But still there are places where the infrastructure cannot be changed and the traffic light semaphores are the only way to control the car flows. In real life, the traffic lights have a predefined plan for change or they receive information from a centralized system when and how they have to change. But what if the traffic lights can cooperate and decide on their own when and how to change? Using this problem, the purpose of the thesis is to explore different agent-based software engineering approaches to design and build a non-conventional distributed system. From the software engineering point of view, the goal of the thesis is to apply the knowledge and use the skills, acquired during the various courses of the master program in Software Engineering, while solving a practical and complex problem such as the traffic in the cities.

A conceptual model of personalized virtual learning environments

The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs. (c) 2005 Elsevier Ltd. All rights reserved.

A tool for a formal pattern modeling language

This paper presents a formal but practical approach for defining and using design patterns. Initially we formalize the concepts commonly used in defining design patterns using Object-Z. We also formalize consistency constraints that must be satisfied when a pattern is deployed in a design model. Then we implement the pattern modeling language and its consistency constraints using an existing modeling framework, EMF, and incorporate the implementation as plug-ins to the Eclipse modeling environment. While the language is defined formally in terms of Object-Z definitions, the language is implemented in a practical environment. Using the plug-ins, users can develop precise pattern descriptions without knowing the underlying formalism, and can use the tool to check the validity of the pattern descriptions and pattern usage in design models. In this work, formalism brings precision to the pattern language definition and its implementation brings practicability to our pattern-based modeling approach.