A Formal Definition of Perfect Bayesian Equilibrium for Extensive Games

Often, perfect bayesian equilibrium is loosely defined by stating that players should be sequentially rational given some beliefs in which Bayes rule is applied “whenever possible”. We show that there are games in which it is not clear what “whenever possible” means. Then, we provide a simple definition of perfect bayesian equilibrium for general extensive games that refines both weak perfect equilibrium and subgame perfect equilibrium.non-cooperative game theory, equilibrium concepts, perfect bayesian, Bayes rule.

Error Cascades in Observational Learning: An Experiment on the Chinos Game

The paper reports an experimental study based on a variant of the popular Chinos game, which is used as a simple but paradigmatic instance of observational learning. There are three players, arranged in sequence, each of whom wins a fixed price if she manages to guess the total number of coins lying in everybody’s hands. Our evidence shows that, despite the remarkable frequency of equilibrium outcomes, deviations from optimal play are also significant. And when such deviations occur, we find that, for any given player position, the probability of a mistake is increasing in the probability of a mistake of her predecessors. This is what we call an error cascade, which we rationalize by way of a simple model of “noisy equilibrium”.positional learning, error cascades

An experimental analysis of team production in networks

Experimental and empirical evidence highlights the role of networks on social outcomes. In this paper we test the properties of exogenously fixed networks in team production. Subjects make the same decisions in a team-work environment under four different organizational networks: The line, the circle, the star, and the complete network. In all the networks, links make information available to neighbors. This design allows us to analyze decisions across networks and a variety of subjects’ types in a standard linear team production game. Contribution levels differ significantly across networks and the star is the most efficient incomplete one. Moreover, our results suggest that subjects act as conditional cooperators with respect to the information received from the network.public goods, networks, experiments

Pooling or fooling? An experiment on signaling

We compare two zero-sum versions of the so called Chinos Game, a traditional parlour game played in many countries. In one version, which we call Preemption Scenario, the first player who guesses right wins the prize. In the alternative version, called the Copycat Scenario, the last player who guesses right wins the prize. While in the Preemption Scenario there is a unique and fully revealing equilibrium, in the Copycat Scenario all equilibria have first movers pool (i.e. hide) their private information. Our experimental evidence shows, however, that in the latter case early movers do not pool but try to fool, i.e. to “lie” by systematically distorting behavior relative to equilibrium play. In fact, doing so they benefit, although the resulting gains diminish as the game proceeds. This highlights the point that, as players adjust their behavior off equilibrium, they also attempt to exploit the induced strategic uncertainty whenever the game allows for this possibility.Financial support from the Spanish Ministry of Economic Development (ECO2014-52345-P and ECO2015-65820-P), Generalitat Valenciana (Research Projects Grupos 3/086) and Instituto Valenciano de Investigaciones Económicas (IVIE) is gratefully acknowledged

Simultaneous Estimation of Vehicle Sideslip and Roll Angles Using an Event-Triggered-Based IoT Architecture

In recent years, there has been a significant integration of advanced technology into the automotive industry, aimed primarily at enhancing safety and ride comfort. While a notable proportion of these driver-assist systems focuses on skid prevention, insufficient attention has been paid to addressing other crucial scenarios, such as rollovers. The accurate estimation of slip and roll angles plays a vital role in ensuring vehicle control and safety, making these parameters essential, especially with the rise of modern technologies that incorporate networked communication and distributed computing. Furthermore, there exists a lag in the transmission of information between the various vehicle systems, including sensors, actuators, and controllers. This paper outlines the design of an IoT architecture that accurately estimates the sideslip angle and roll angle of a vehicle, while addressing network transmission delays with a networked control system and an event-triggered communication scheme. Experimental results are presented to validate the performance of the IoT architecture proposed. The event-triggered scheme of the IoT solution is used to decrease data transmission and prevent network overload.Funding. Grant [ PID2022-136468OB-I00 ] funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”

Algunas evidencias de aplicación

Libro temático especializadoLa sustentabilidad también debe aplicarse al sistema de producción, buscando impulsar transformaciones graduales de los estilos y modelos productivos tradicionales a unas de mayor eficiencia. Y donde se incorpore la dimensión ambiental y geográfico-espacial, para crear estructuras productivas más progresivas y equitativas en las sociedades. Todo esto, como alternativa para revertir las tendencias de escasez y agotamiento de los recursos naturales, así como de los desequilibrios globales, cuyos costos permean todos los tejidos humanos. De esta manera, la “sustentabilidad productiva” se concibe como la generación de bienes y servicios con ciertos estándares de calidad, bajo un esquema de eficiencia, rendimiento y de organización inclusiva e integrada, con baja presión al ambiente y uso racional de los recursos, garantizando la estadía y permanencia de los insumos y materiales en el tiempo. Desde esta perspectiva, la producción sustentable y el crecimiento de largo plazo pueden ser explicados por la capacidad que tienen las economías para generar e incorporar conocimientos y tecnologías. De ahí que, la educación y las cualificaciones del capital humano, los cambios en la organización de la producción y la calidad institucional, sean elementos nodales para avanzar en la consolidación de este ambiente productivo

Parasitología Interactiva

Desarrollo de una guía interactiva donde se muestran los ciclos biológicos,imágenes y dibujos de los estadios evolutivos de los principales géneros y especies de parásitos protozoos relevantes en al ámbito veterinario

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014–2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V