Smith and Rawls share a room

We consider one-to-one matching (roommate) problems in which agents (students) can either be matched as pairs or remain single. The aim of this paper is twofold. First, we review a key result for roommate problems (the ``lonely wolf'' theorem) for which we provide a concise and elementary proof. Second, and related to the title of this paper, we show how the often incompatible concepts of stability (represented by the political economist Adam Smith) and fairness (represented by the political philosopher John Rawls) can be reconciled for roommate problems.

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

Materials nanocomposits a partir de whiskers de cel•lulosa i matriu polimèrica de cautxú

De acuerdo con los objetivos generales del proyecto y plan de trabajo previsto, para esta anualidad, se obtuvieron fibras y microfibras de celulosa a partir de dos fuentes: celulosa vegetal de pino y eucalipto y celulosa bacterial. Las microfibrillas han sido utilizadas como material de refuerzo para la fabricación de materiales compuestos a partir de caucho natural, policaprolactona y polivinil alcohol. Las muestras se fabricaron mediante la técnica de "casting" en medio acuoso y temperatura ambiente. Las muestras fueron caracterizados en sus propiedades mecánicas, físicas y térmicas. Se observó que, en general, la adición de las microfibrillas de celulosa en las matrices poliméricas provoca una mejora sustancial en las propiedades mecánicas del material en comparación con el polímero sin reforzar. Los resultados pueden resumirse de la siguiente manera: 1.Fabricación de materiales compuestos a base de caucho natural y fibras de celulosa. Se obtuvieron fibras y nanofibras de celulosa que fueron modificadas químicamente y usadas como refuerzo en matriz de caucho. Los resultados mostraron mejora de propiedades mecánicas del material, principalmente en los materiales compuestos reforzados con nanofibras. 2. Obtención de whiskers de celulosa y su utilización como material de refuerzo en una matriz de policaprolactona. Se obtuvieron whiskers de celulosa a partir de pasta blanqueada. La adición en una matriz de policaprolactona produjo materiales compuestos con propiedades mecánicas superiores a la matriz, con buena dispersión de los whiskers. 3. Obtención de fibras de celulosa bacterial y nanofibras de celulosa, aislamiento y utilización sobre una matriz de polivinil alcohol. Se obtuvo celulosa bacterial a partir de la bacteria Gluconacetobacter xylinum. Además se fabricaron nanofibras de celulosa a partir eucalipto blanqueado. La celulosa bacterial como material de refuerzo no produjo importantes mejoras en las propiedades mecánicas de la matriz; en cambio se observaron mejoras destacables con la nanofibra como refuerzo.

Management of corn stalk waste as reinforcement for polypropylene injection moulded composites

The main objective of this study was the management of corn stalk waste as reinforcement for polypropylene (PP) injection moulded composites as an alternative to wood flour and fibers. In the first step, corn stalk waste was subjected to various treatments, and four different corn stalk derivatives (flour and fibers) able to be used as reinforcement of composite materials were prepared and characterized. These derivatives are corn stalk flour, thermo-mechanical, semi-chemical, and chemical fibers. They were characterized in terms of their yield, lignin content, Kappa number, fiber length/diameter ratio, fines, coarseness, viscosity, and the length at the break of a standard sheet of paper. Results showed that the corn stalk derivatives have different physico-chemical properties. In the second step, the prepared flour and fibers were explored as a reinforcing element for PP composites. Coupled and non-coupled PP composites were prepared and tested for tensile properties. For overall trend, with the addition of a coupling agent, tensile properties of composites significantly improved, as compared with non-coupled samples. In addition, a morphological study revealed the positive effect of the coupling agent on the interfacial bonding. The composites prepared with semichemical fiber gave better results in comparison with the rest of the corn stalk derivatives due to its chemical characteristics

CB1 cannabinoid receptor modulates MDMA acute responses and reinforcement

Background: 3, 4-methylenedioxymethamphetamine (MDMA) is a popular recreational drug widely abused by young people. The endocannabinoid system is involved in the addictive processes induced by different drugs of abuse. However, the role of this system in the pharmacological effects of MDMA has not been yet clarified.Methods: Locomotion, body temperature and anxiogenic-like responses were evaluated after acute MDMA administration in CB1 knockout mice. Additionally, MDMA rewarding properties were investigated in the place conditioning and the intravenous self-administration paradigms. Extracellular levels of DA in the nucleus accumbens were also analyzed after a single administration of MDMA by in vivo microdialysis. Results: Acute MDMA administration increased locomotor activity, body temperature and anxiogenic-like responses in wild type mice, but these responses were lower or abolished in knockout animals. MDMA produced similar conditioned place preference and increased dopamine extracellular levels in the nucleus accumbens in both genotypes. Nevertheless, CB1 knockout mice failed to self-administer MDMA at any of the doses used. Conclusions: These results indicate that CB1 cannabinoid receptors play an important role in the acute prototypical effects of MDMA, and are essential in the acquisition of an operant behavior to self-administer this drug.

Impedance boundary conditions for pseudo-spectral time-domain methods in room acoustics

The pseudo-spectral time-domain (PSTD) method is an alternative time-marching method to classicalleapfrog finite difference schemes in the simulation of wave-like propagating phenomena. It is basedon the fundamentals of the Fourier transform to compute the spatial derivatives of hyperbolic differential equations. Therefore, it results in an isotropic operator that can be implemented in an efficient way for room acoustics simulations. However, one of the first issues to be solved consists on modeling wallabsorption. Unfortunately, there are no references in the technical literature concerning to that problem. In this paper, assuming real and constant locally reacting impedances, several proposals to overcome this problem are presented, validated and compared to analytical solutions in different scenarios.

Impedance boundary conditions for pseudo-spectral time-domain methods in room acoustics

The Pseudo-Spectral Time Domain (PSTD) method is an alternative time-marching method to classical leapfrog finite difference schemes inthe simulation of wave-like propagating phenomena. It is based on the fundamentals of the Fourier transform to compute the spatial derivativesof hyperbolic differential equations. Therefore, it results in an isotropic operator that can be implemented in an efficient way for room acousticssimulations. However, one of the first issues to be solved consists on modeling wall absorption. Unfortunately, there are no references in thetechnical literature concerning to that problem. In this paper, assuming real and constant locally reacting impedances, several proposals toovercome this problem are presented, validated and compared to analytical solutions in different scenarios.

Survival and Sensemaking: Organizational Resilience in a Wall Street Trading Room After 9/11

How do organizations cope with extreme uncertainty? The existing literature is divided on this issue: some argue that organizations deal best with uncertainty in the environment by reproducing it in the organization, whereas others contend that the orga nization should be protected from the environment. In this paper we study the case of a Wall Street investment bank that lost its entire office and trading technology in the terrorist attack of September 11 th. The traders survived, but were forced to relocate to a makeshift trading room in New Jersey. During the six months the traders spent outside New York City, they had to deal with fears and insecurities inside the company as well as outside it: anxiety about additional attacks, questions of professional identity, doubts about the future of the firm, and ambiguities about the future re-location of the trading room. The firm overcame these uncertainties by protecting the traders' identities and their ability to engage in sensemaking. The organization held together through a leadership style that managed ambiguities and created the conditions for new solutions to emerge.

Ecologies of Value in a Wall Street Trading Room

Our task in this paper is to analyze the organization of trading in the era of quantitative finance. To do so, we conduct an ethnography of arbitrage, the trading strategy that best exemplifies finance in the wake of the quantitative revolution. In contrast to value and momentum investing, we argue, arbitrage involves an art of association-the construction of equivalence (comparability) of properties across different assets. In place of essential or relational characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else-associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.

Resolving identities: Successive crises in a trading room after 9/11

How do organizations cope with extreme uncertainty? The existing literatureis divided on this issue: some argue that organizations deal best withuncertainty in the environment by reproducing it in the organization, whereasothers contend that the orga nization should be protected from theenvironment. In this paper we study the case of a Wall Street investment bankthat lost its entire office and trading technology in the terrorist attack ofSeptember 11 th. The traders survived, but were forced to relocate to amakeshift trading room in New Jersey. During the six months the traders spentoutside New York City, they had to deal with fears and insecurities insidethe company as well as outside it: anxiety about additional attacks,questions of professional identity, doubts about the future of the firm, andambiguities about the future re-location of the trading room. The firmovercame these uncertainties by protecting the traders identities and theirability to engage in sensemaking. The organization held together through aleadership style that managed ambiguities and created the conditions for newsolutions to emerge.

How to recognize opportunities: Heterarchical search in a Wall Street trading room

Our task in this paper is to analyze the organization of trading in the era of quantitativefinance. To do so, we conduct an ethnography of arbitrage, the trading strategy that bestexemplifies finance in the wake of the quantitative revolution. In contrast to value andmomentum investing, we argue, arbitrage involves an art of association - the constructionof equivalence (comparability) of properties across different assets. In place of essentialor relationa l characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else - associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.