Teaching an Old Robot New Tricks: Learning Novel Tasks via Interaction with People and Things

As AI has begun to reach out beyond its symbolic, objectivist roots into the embodied, experientialist realm, many projects are exploring different aspects of creating machines which interact with and respond to the world as humans do. Techniques for visual processing, object recognition, emotional response, gesture production and recognition, etc., are necessary components of a complete humanoid robot. However, most projects invariably concentrate on developing a few of these individual components, neglecting the issue of how all of these pieces would eventually fit together. The focus of the work in this dissertation is on creating a framework into which such specific competencies can be embedded, in a way that they can interact with each other and build layers of new functionality. To be of any practical value, such a framework must satisfy the real-world constraints of functioning in real-time with noisy sensors and actuators. The humanoid robot Cog provides an unapologetically adequate platform from which to take on such a challenge. This work makes three contributions to embodied AI. First, it offers a general-purpose architecture for developing behavior-based systems distributed over networks of PC's. Second, it provides a motor-control system that simulates several biological features which impact the development of motor behavior. Third, it develops a framework for a system which enables a robot to learn new behaviors via interacting with itself and the outside world. A few basic functional modules are built into this framework, enough to demonstrate the robot learning some very simple behaviors taught by a human trainer. A primary motivation for this project is the notion that it is practically impossible to build an "intelligent" machine unless it is designed partly to build itself. This work is a proof-of-concept of such an approach to integrating multiple perceptual and motor systems into a complete learning agent.

Optimizing Product Line Designs: Efficient Methods and Comparisons

We compare a broad range of optimal product line design methods. The comparisons take advantage of recent advances that make it possible to identify the optimal solution to problems that are too large for complete enumeration. Several of the methods perform surprisingly well, including Simulated Annealing, Product-Swapping and Genetic Algorithms. The Product-Swapping heuristic is remarkable for its simplicity. The performance of this heuristic suggests that the optimal product line design problem may be far easier to solve in practice than indicated by complexity theory.

Lecture 4 - Methods and Stuff

Banking Parameters and arguments Passing Objects Primitives Returning Getters and Setters

Strategies for teaching students with special needs : methods and techniques for classroom instruction.

El objetivo de este manual es que orientar a los maestros de primaria en centros de integración que tienen en su clase niños con necesidades especiales. Las estrategias presentadas intencionadamente borran la distinción entre y dentro de las categorías de niños con necesidades especiales y hacen hincapié en el acto de aprender de todos los niños. Tanto las estrategias como las prácticas educativas son reales, con énfasis sobre las orientaciones de lo que se debe hacer para satisfacer las necesidades de veinticinco estudiantes muy distintos. La atención se centra en la evaluación de lectura y métodos de lectura, el lenguaje, las matemáticas y las ideas de los aspectos sociales de integración.

Catalase in fluvial biofilms: a comparison between different extraction methods and example of application in a metal-polluted river

Antioxidant enzymes are involved in important processes of cell detoxification during oxidative stress and have, therefore, been used as biomarkers in algae. Nevertheless, their limited use in fluvial biofilms may be due to the complexity of such communities. Here, a comparison between different extraction methods was performed to obtain a reliable method for catalase extraction from fluvial biofilms. Homogenization followed by glass bead disruption appeared to be the best compromise for catalase extraction. This method was then applied to a field study in a metal-polluted stream (Riou Mort, France). The most polluted sites were characterized by a catalase activity 4–6 times lower than in the low-polluted site. Results of the comparison process and its application are promising for the use of catalase activity as an early warning biomarker of toxicity using biofilms in the laboratory and in the field

Development of molecular monitoring methods and assessment of the environmental fate of the biological control agent of fire blight Pseudomonas fluorescens EPS62e

Pseudomonas fluorescens EPS62e es va seleccionar com a agent de biocontrol del foc bacterià per la seva eficàcia en el control de Erwinia amylovora. En aquest treball es van desenvolupar mètodes de traçabilitat que van permetre la seva detecció específica i quantificació. Mitjançant les tècniques RAPD i U-PCR es van obtenir fragments d'amplificació diferencial per EPS62e que es van seqüenciar i caracteritzar com marcadors SCAR per dissenyar una PCR en temps real. La PCR a temps real es va utilitzar simultàniament amb mètodes microbiològics per estudiar l'adaptabilitat epifítica de EPS62e en pomera i perera. L'ús combinat de mètodes microbiològics i moleculars va permetre la identificació de tres estats fisiològics de EPS62e: la colonització activa, l'entrada en un estat de viable però no cultivable, i la mort cel·lular. Aquest treball mostra que EPS62e està ben adaptada a la colonització de flors a camp, encoratjant la seva utilització dins d'una estratègia de control biològic contra el foc bacterià.

Methods and resources for climate impacts research: achieving synergy

The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.