Evolving artificial neural networks applied to generate virtual characters

Computer game industry is one of the most prof­ itable nowadays. Although this industry has evolved fast in the last years in different fields, Artificial Intelligence (AI) seems to be stuck. Many games still make use of simple state machines to simulate AI. New models can be designed and proposed to replace this jurassic technique. In this paper we propose the use of Artificial Neural Networks (ANN) as a new model. ANN will be then in charge of receiving information from the game (sensors) and carry out actions (actuators) according to the information received. The search for the best ANN is a complex task that strongly affects the task performance while often requiring a high computational time. In this work, we present ADANN, a system for the automatic evolution and adaptation of artificial neural networks based on evolutionary ANN (EANN). This approach use Genetic Algorithm (GA) that evolves fully connected Artificial Neural Network. The testing game is called Unreal Tournament 2004. The new agent obtained has been put to the test jointly with CCBot3, the winner of BotPrize 2010 competition [1], and have showed a significant improvement in the humannesss ratio. Additionally, we have confronted our approach and CCBot3 (winner of BotPrize competition in 2010) to First-person believability assessment (BotPrize original judging protocol), demonstrating that the active involvement of the judge has a great impact in the recognition of human-like behaviour

Artificial intelligence approaches for the generation and assessment of believable human-like behaviour in virtual characters

Having artificial agents to autonomously produce human-like behaviour is one of the most ambitious original goals of Artificial Intelligence (AI) and remains an open problem nowadays. The imitation game originally proposed by Turing constitute a very effective method to prove the indistinguishability of an artificial agent. The behaviour of an agent is said to be indistinguishable from that of a human when observers (the so-called judges in the Turing test) can not tell apart humans and non-human agents. Different environments, testing protocols, scopes and problem domains can be established to develop limited versions or variants of the original Turing test. In this paper we use a specific version of the Turing test, based on the international BotPrize competition, built in a First-Person Shooter video game, where both human players and non-player characters interact in complex virtual environments. Based on our past experience both in the BotPrize competition and other robotics and computer game AI applications we have developed three new more advanced controllers for believable agents: two based on a combination of the CERA-CRANIUM and SOAR cognitive architectures and other based on ADANN, a system for the automatic evolution and adaptation of artificial neural networks. These two new agents have been put to the test jointly with CCBot3, the winner of BotPrize 2010 competition [1], and have showed a significant improvement in the humanness ratio. Additionally, we have confronted all these bots to both First-person believability assessment (BotPrize original judging protocol) and Third-person believability assess- ment, demonstrating that the active involvement of the judge has a great impact in the recognition of human-like behaviour.MICINN -Ministerio de Ciencia e Innovación(FCT-13-7848

Live cell-lineage tracing and machine learning reveal patterns of organ regeneration.

Despite the intrinsically stochastic nature of damage, sensory organs recapitulate normal architecture during repair to maintain function. Here we present a quantitative approach that combines live cell-lineage tracing and multifactorial classification by machine learning to reveal how cell identity and localization are coordinated during organ regeneration. We use the superficial neuromasts in larval zebrafish, which contain three cell classes organized in radial symmetry and a single planar-polarity axis. Visualization of cell-fate transitions at high temporal resolution shows that neuromasts regenerate isotropically to recover geometric order, proportions and polarity with exceptional accuracy. We identify mediolateral position within the growing tissue as the best predictor of cell-fate acquisition. We propose a self-regulatory mechanism that guides the regenerative process to identical outcome with minimal extrinsic information. The integrated approach that we have developed is simple and broadly applicable, and should help define predictive signatures of cellular behavior during the construction of complex tissues

REIRE : revista d'innovació i recerca en educació

Resumen basado en el de la publicaciónSe pretende averiguar la coherencia de la formación recibida por los maestros de educación musical que han estudiado en la UB (Universidad de Barcelona) respecto a los requisitos necesarios para su inserción laboral. Es un estudio descriptivo ex post facto por encuesta que ha dado como resultados un perfil definido de titulado que indica un alto grado de inserción laboral y un tiempo de espera mínimo, principalmente en las escuelas públicas y mediante oposiciones o bolsas de interinos. Estos maestros están satisfechos de su trabajo, y la motivación para aprender, la capacidad de trabajo, la comunicación oral, la vocación, la responsabilidad o las habilidades sociales son algunas de las competencias profesionales que creen que han sido determinantes a la hora de ser contratados. Por todo esto se concluye que las personas que han cursado los estudios Maestro de Educación Musical de la UB tienen un alto grado de inserción y satisfacción laboral, y que la formación inicial coincide en gran parte con las competencias de la profesión detectadas en este estudio.CataluñaES

Aula abierta

Resumen tomado de la publicaciónEste trabajo analiza el impacto que la evaluación formativa y participativa en docencia universitaria ha tenido en las revistas españolas. Para ello se presentan los resultados de un estudio basado en contabilizar el número de artículos publicados entre 1999 y 2009, y en analizar el contenido de cuatro artículos seleccionados del total de trabajos recogidos tras las búsquedas efectuadas con la base de datos del CSIC (ISOC-educación). Las principales conclusiones se refieren a que apenas existen publicaciones referidas a la evaluación formativa y participativa en la universidad, y a que la mayoría de estas contribuciones, si bien describen y valoran cómo se han implementado y aplicado en diversos centros universitarios, apenas aportan evidencias que confirmen pertinencia y viabilidad.AsturiasUniversidad de Oviedo. Facultad de Formación del Profesorado y Educación; Calle Aniceto Sela, s. n.; 33005 Oviedo; Tel. +34985103215; Fax +34985103214; [email protected]