Ethical trust and social moral norms simulation : a bio-inspired agent-based modelling approach

The understanding of the micro-macro link is an urgent need in the study of social systems. The complex adaptive nature of social systems adds to the challenges of understanding social interactions and system feedback and presents substantial scope and potential for extending the frontiers of computer-based research tools such as simulations and agent-based technologies. In this project, we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the development of collective social moral norms as representative sample of the bigger micro-macro link of social systems. We outline our computational model of ethical trust (CMET) informed by research findings from trust, machine ethics and neural science. Guided by the CMET architecture, we discuss key implementation ideas for the simulations of ethical trust and social moral norms.

Organisational learning as an emerging process: the generative role of digital tools in informal learning practices

 Increasing attention is paid to organisational learning, with the success of contemporary organisations strongly contingent on their ability to learn and grow. Importantly, informal learning is argued to be even more significant than formal learning initiatives. Given the widespread use of digital technologies in the workplace, what requires further attention is how digital technologies (eg, massive open online courses—MOOC) enable informal learning processes. Drawing from Complex Adaptive Systems (CAS) theory, in this paper we advance a conceptual model for examining this important topic. The two dimensional matrix and the micro-level description of informal learning activities presented provide a framework for both further research on technology-mediated practices for informal learning, as well as the design of formative contexts for learning to occur.

Modelo de organização adaptável a cenários turbulentos: setor empresarial energético brasileiro

O cenário geopolítico global de desenvolvimento assimétrico e novas fontes de energia constituem um desafio para a sustentabilidade organizacional, requerendo organizações com capacidade de adaptação a ambientes turbulentos. Os principais aspectos que afetam a sobrevivência das empresas de energia podem ser categorizados em geopolíticos, econômicos, sociais, tecnológicos, legais, ambientais, de segurança, de energia e administrativos. Esta tese doutoral apresenta um modelo de organizações com capacidade de adaptação a ambientes turbulentos que permite à empresa atingir sustentabilidade no tempo, como resposta à pergunta de partida. Essa pergunta procura as características determinantes de um modelo de organização adaptável, considerando o setor energético brasileiro, no cenário geopolítico global de desenvolvimento assimétrico e novas fontes de energia, segundo a percepção de gestores. A metodologia adotada tomou por base a Grounded Theory apoiada pelo software Atlas/ti e aplicada a entrevistas em profundidade. O método utilizado permitiu construir a teoria indutivamente, com base em categorias, propriedades e dimensões. O modelo proposto emergiu da pesquisa configurando a capacidade de adaptação aos cenários turbulentos para atingir sustentabilidade organizacional como fundamentada nas categorias de Planejamento Prospectivo, Sistemas Adaptativos e Integração Estrutural, identificando as propriedades e dimensões requeridas em cada uma dessas categorias.

Fragmentos de complexidade aplicados ao mercado financeiro

O aumento da complexidade do mercado financeiro tem sido relatado por Rajan (2005), Gorton (2008) e Haldane e May (2011) como um dos principais fatores responsáveis pelo incremento do risco sistêmico que culminou na crise financeira de 2007/08. O Bank for International Settlements (2013) aborda a questão da complexidade no contexto da regulação bancária e discute a comparabilidade da adequação de capital entre os bancos e entre jurisdições. No entanto, as definições dos conceitos de complexidade e de sistemas adaptativos complexos são suprimidas das principais discussões. Este artigo esclarece alguns conceitos relacionados às teorias da Complexidade, como se dá a emergência deste fenômeno, como os conceitos podem ser aplicados ao mercado financeiro. São discutidas duas ferramentas que podem ser utilizadas no contexto de sistemas adaptativos complexos: Agent Based Models (ABMs) e entropia e comparadas com ferramentas tradicionais. Concluímos que ainda que a linha de pesquisa da complexidade deixe lacunas, certamente esta contribui com a agenda de pesquisa econômica para se compreender os mecanismos que desencadeiam riscos sistêmicos, bem como adiciona ferramentas que possibilitam modelar agentes heterogêneos que interagem, de forma a permitir o surgimento de fenômenos emergentes no sistema. Hipóteses de pesquisa são sugeridas para aprofundamento posterior.

Reengenharia do framework cosmos: uma solução para prover suporte e adaptações abertas.

Self-adaptive software system is able to change its structure and/or behavior at runtime due to changes in their requirements, environment or components. One way to archieve self-adaptation is the use a sequence of actions (known as adaptation plans) which are typically defined at design time. This is the approach adopted by Cosmos - a Framework to support the configuration and management of resources in distributed environments. In order to deal with the variability inherent of self-adaptive systems, such as, the appearance of new components that allow the establishment of configurations that were not envisioned at development time, this dissertation aims to give Cosmos the capability of generating adaptation plans of runtime. In this way, it was necessary to perform a reengineering of the Cosmos Framework in order to allow its integration with a mechanism for the dynamic generation of adaptation plans. In this context, our work has been focused on conducting a reengineering of Cosmos. Among the changes made to in the Cosmos, we can highlight: changes in the metamodel used to represent components and applications, which has been redefined based on an architectural description language. These changes were propagated to the implementation of a new Cosmos prototype, which was then used for developing a case study application for purpose of proof of concept. Another effort undertaken was to make Cosmos more attractive by integrating it with another platform, in the case of this dissertation, the OSGi platform, which is well-known and accepted by the industry

Instanciação e avaliação de um framework para a geração dinâmica de processos

One way to deal with the high complexity of current software systems is through selfadaptive systems. Self-adaptive system must be able to monitor themselves and their environment, analyzing the monitored data to determine the need for adaptation, decide how the adaptation will be performed, and finally, make the necessary adjustments. One way to perform the adaptation of a system is generating, at runtime, the process that will perform the adaptation. One advantage of this approach is the possibility to take into account features that can only be evaluated at runtime, such as the emergence of new components that allow new architectural arrangements which were not foreseen at design time. In this work we have as main objective the use of a framework for dynamic generation of processes to generate architectural adaptation plans on OSGi environment. Our main interest is evaluate how this framework for dynamic generation of processes behave in new environments

Using network connectance and autonomy analyses to uncover patterns of photosynthetic responses in tropical woody species

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Urban Traffic Control and Monitoring - An Approach for the Brazilian Intelligent Cities Project

This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

Continuity and Change in New Products

This doctoral dissertation is triggered by an emergent problem: how can firms reinvent themselves? Continuity- and change-oriented decisions fundamentally shape overtime the activities and potential revenues of organizations and other adaptive systems, but both types of actions draw upon limited resources and rely on different organizational routines and capabilities. Most organizations appear to have difficulties in making tradeoffs, so that it is easier to overinvest in one of them than to successfully achieve a mixture of both. Nevertheless, theory and empirical evidence suggest that too little of either may reduce performance, indicating a need to learn more about how organizations reconcile these tensions. In the first paper, I moved from the consideration that rapid changes in competitive environments increasingly require firms to be “ambidextrous” implementing organizational mechanisms and structures that allow continuity- and change-oriented activities to be engaged at the same time. More specifically, I show that continuity- and change-related decisions can’t be confined either inside or outside the firm, but span overtime across distinct decision domains located within and beyond the organizational boundaries. Reconciling static and dynamic perspectives of ambidexterity, I conceptualize a firm’s strategy as a bundle of decisions about product attributes and components of the production team, proposing a multidimensional and dynamic model of structural ambidexterity that explains why and how firms could manage conflicting pressures for continuity and change in the context of new products. In the second study I note how rigorous systematic evidence documenting the success of ambidextrous organizations is lacking, and there has been very little investigation of how firms deal with continuity and change in new products. How to manage the transition form a successful product to another? What to change and what to keep? Incumbents that deal with series of products over time need to update their offerings in order to have the most relevant attributes to prospect clients without disappoint the current customer base. They need to both match and anticipate consumers’ preferences, blending something old with something new to satisfy the current demand and enlarge the herd by appealing to newer audiences. This paper contributes to strategic renewal and ambidexterity-related research with the first empirically assessment of a positive consumer response to ambidexterity in new products. Also, this study provides a practical method to monitor overtime the degree to which a brand or a firm is continuity- or change- oriented and evaluate different strategy profiles across two decision domains that play a pivotal role in new products: product attributes and components of the production team.

Climate Change Adaptation Tool for Transportation: Mid-Atlantic Region Case Study

Transportation has contributed to climate change and will most likely be impacted by changes in sea level, temperature, precipitation, and wind, for example. As the risk of climate change impacts become more imminent, pressure for adaptation within transportation agencies to address these impacts continues to rise. The most logical strategy is to integrate consideration of adaptation projects into the long-range transportation planning (LRTP) process. To do this, tools and experience are needed to assist transportation agencies. The Climate Change Adaptation Tool for Transportation (CCATT) is a step-by-step method to evaluate climate change scenarios and impacts, inventory at-risk existing and proposed infrastructure, and assess mitigation practices to identify supporting adaptation efforts. This paper focuses on the application of CCATT to the Mid-Atlantic region using a case study on the Wilmington Area Planning Council (WILMAPCO), the Metropolitan Planning Organization for northern Delaware. The results of the application and case study demonstrate the importance of climate change adaptation practices in long-range transportation planning. DOI: 10.1061/(ASCE)TE.1943-5436.0000515. (C) 2013 American Society of Civil Engineers.

Model-Centric, Context-Aware Software Adaptation

Software must be constantly adapted to changing requirements. The time scale, abstraction level and granularity of adaptations may vary from short-term, fine-grained adaptation to long-term, coarse-grained evolution. Fine-grained, dynamic and context-dependent adaptations can be particularly difficult to realize in long-lived, large-scale software systems. We argue that, in order to effectively and efficiently deploy such changes, adaptive applications must be built on an infrastructure that is not just model-driven, but is both model-centric and context-aware. Specifically, this means that high-level, causally-connected models of the application and the software infrastructure itself should be available at run-time, and that changes may need to be scoped to the run-time execution context. We first review the dimensions of software adaptation and evolution, and then we show how model-centric design can address the adaptation needs of a variety of applications that span these dimensions. We demonstrate through concrete examples how model-centric and context-aware designs work at the level of application interface, programming language and runtime. We then propose a research agenda for a model-centric development environment that supports dynamic software adaptation and evolution.

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems.