Scalable and Energy Efficient Software Architecture for Human Behavioral Measurements

Understanding human behavior is central to many professions including engineering, health and the social sciences, and has typically been measured through surveys, direct observation and interviews. However, these methods are known to have drawbacks, including bias, problems with recall accuracy, and low temporal fidelity. Modern mobile phones have a variety of sensors that can be used to find activity patterns and infer the underlying human behaviors, placing a heavy load on the phone's battery. Social science researchers hoping to leverage this new technology must carefully balance the fidelity of the data with the cost in phone performance. Crucially, many of the data collected are of limited utility because they are redundant or unnecessary for a particular study question. Previous researchers have attempted to address this problem by modifying the measurement schedule based on sensed context, but a complete solution remains elusive. In the approach described here, measurement is made contingent on sensed context and measurement objectives through extensions to a configuration language, allowing significant improvement to flexibility and reliability. Empirical studies indicate a significant improvement in energy efficiency with acceptable losses in data fidelity

Defeasible decision making in a robotic environment

Decision making models for autonomous agents are recently receiving increased attention, particularly in the feld of intelligent robots. This work presents a Defeasible Logic Programming approach to decision making in an environment with single and multiple robots. We will show, how a successful tool for knowledge representation and defeasible reasoning could be applied to the problem of deciding which task should be performed next. Besides, we will explain with detailed examples how the decision process is performed when there is only one robot in the environment, and then we will consider how the same robot decides when there are more robots working in the environment.Actualmente, los modelos de toma de decisiones para agentes autónomos están recibiendo mucha atención, particularmente en el área de robots inteligentes. Este trabajo presenta un enfoque basado en Programación en Lógica Rebatible para la toma de decisiones en un ambiente con un único robot y con múltiples robots. Mostraremos como una herramienta exitosa para la representación de conocimiento y razonamiento rebatible, puede ser aplicada al problema de decidir que tarea debe ser realizada a continuación. Además, explicaremos con ejemplos detallados como se realiza el proceso de decisión cuando hay solamente un robot en el ambiente, y luego consideraremos como decide el mismo robot cuando hay otros robots presentes en el ambiente.VIII Workshop de Procesamiento Distribuido y ParaleloRed de Universidades con Carreras en Informática (RedUNCI

Agar--an animal construction kit

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1989.Includes bibliographical references.by Michael D. TraversM.S

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

C-EMO: A Modeling Framework for Collaborative Network Emotions

Recent research in the area of collaborative networks is focusing on the social and organizational complexity of collaboration environments as a way to prevent technological failures and consequently contribute for the collaborative network’s sustainability. One direction is moving towards the need to provide “human-tech” friendly systems with cognitive models of human factors such as stress, emotion, trust, leadership, expertise or decision-making ability. In this context, an emotion-based system is being proposed with this thesis in order to bring another approach to avoid collaboration network’s failures and help in the management of conflicts. This approach, which is expected to improve the performance of existing CNs, adopts some of the models developed in the human psychology, sociology and affective computing areas. The underlying idea is to “borrow” the concept of human-emotion and apply it into the context of CNs, giving the CN players the ability to “feel emotions”. Therefore, this thesis contributes with a modeling framework that conceptualizes the notion of “emotion” in CNs and a methodology approach based on system dynamics and agent-based techniques that estimates the CN player’s “emotional states” giving support to decision-making processes. Aiming at demonstrating the appropriateness of the proposed framework a simulation prototype was implemented and a validation approach was proposed consisting of simulation of scenarios, qualitative assessment and validation by research community peers.Recentemente a área de investigação das redes colaborativas tem vindo a debruçar-se na complexidade social e organizacional em ambientes colaborativos e como pode ser usada para prevenir falhas tecnológicas e consequentemente contribuir para redes colaborativas sustentáveis. Uma das direcções de estudo assenta na necessidade de fornecer sistemas amigáveis “humano-tecnológicos” com modelos cognitivos de factores humanos como o stress, emoção, confiança, liderança ou capacidade de tomada de decisão. É neste contexto que esta tese propõe um sistema baseado em emoções com o objectivo de oferecer outra aproximação para a gestão de conflitos e falhas da rede de colaboração. Esta abordagem, que pressupõe melhorar o desempenho das redes existentes, adopta alguns dos modelos desenvolvidos nas áreas da psicologia humana, sociologia e affective computing. A ideia que está subjacente é a de “pedir emprestado” o conceito de emoção humana e aplicá-lo no contexto das redes colaborativas, dando aos seus intervenientes a capacidade de “sentir emoções”. Assim, esta tese contribui com uma framework de modelação que conceptualiza a noção de “emoção” em redes colaborativas e com uma aproximação de metodologia sustentada em sistemas dinâmicos e baseada em agentes que estimam os “estados emocionais” dos participantes e da própria rede colaborativa. De forma a demonstrar o nível de adequabilidade da framework de modelação proposta, foi implementado um protótipo de simulação e foi proposta uma abordagem de validação consistindo em simulação de cenários, avaliação qualitativa e validação pelos pares da comunidade científica

The Invention of Good Games: Understanding Learning Design in Commercial Videogames

This work sought to help inform the design of educational digital games by the studying the design of successful commercial videogames. The main thesis question was: How does a commercially and critically successful modern video game support the learning that players must accomplish in order to succeed in the game (i.e. get to the end or win)? This work takes a two-pronged approach to supporting the main argument, which is that the reason we can learn about designing educational games by studying commercial games is that people already learn from games and the best ones are already quite effective at teaching players what they need to learn in order to succeed in the game. The first part of the research establishes a foundation for the argument, namely that accepted pedagogy can be found in existing commercial games. The second part of the work proposes new methods for analysing games that can uncover mechanisms used to support learning in games which can be employed even if those games were not originally designed as educational objects. In order to support the claim that ‘good’ commercial videogames already embody elements of sound pedagogy an explicit connection is made between game design and formally accepted theory and models in teaching and learning. During this phase of the work a significant concern was raised regarding the classification of games as ‘good’, so a new methodology using Borda Counts was devised and tested that combines various disjoint subjective reviews and rankings from disparate sources in non-trivial manner that accounts for relative standings. Complementary to that was a meta-analysis of the criteria used to select games chosen as subjects of study as reported by researchers. Then, several games were chosen using this new ranking method and analysed using another new methodology that was designed for this work, called Instructional Ethology. This is a new methodology for game design deconstruction and analysis that would allows the extraction of information about mechanisms used to support learning. This methodology combines behavioural and structural analysis to examine how commercial games support learning by examining the game itself from the perspective of what the game does. Further, this methodology can be applied to the analysis of any software system and offers a new approach to studying any interactive software. The results of the present study offered new insights into how several highly successful commercial games support players while they learn what they must learn in order to succeed in those games. A new design model was proposed, known as the 'Magic Bullet' that allows designers to visualize the relative proportions of potential learning in a game to assess the potential of a design

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version