997 resultados para Reinforcement material


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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

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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

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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

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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

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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

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El propósito de esta monografía es explicar de qué manera la adquisición de material bélico de la administración Chávez desde el año 2004 al 2008, influyen en la relación bilateral Venezuela-Estados Unidos.

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El proyecto se plantea para elaborar un itinerario educativo partiendo de una idea fundamental, conocer Asturias, partiendo de conocer el medio m??s pr??ximo a ellos, en este caso Avil??s. Como complemento al material escrito, se va a elaborar un v??deo, diapositivas y transparencias que sirvan par realizar actividades en el aula sin olvidar las visitas que los alumnos hagan a los sitios m??s representativos. Se presenta una memoria con diapositivas, un v??deo did??ctico y un master para realizar otras copias originales. Los contenidos del proyecto son: introducci??n al estudio de Avil??s desde el Monte de la Luz; localizaci??n y concejos lim??trofes; estudio de la estructura de la villa; la ria de Avil??s; estudio de la econom??a; el Monte de la Luz; instalaciones como Ensidesa; monumentos; escudo de Avil??s; posibilidades de ocio en Avil??s.. En la memoria el recorrido se hace a trav??s de la historia, desde la Prehistoria hasta la actualidad. Los autores son profesores de centros adscritos al CEP de Avil??s.

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Se intenta difundir en todos los Centros del CEP un diaporama con sonido y una colecci??n de diapositivas sobre la cer??mica negra de Llamas de Mouro, por ser una de las principales muestras artesanles de la cultura asturiana, con el fin de permitir al alumno una mayor y mejor conocimiento de su realidad inmediata. No se cumplieron todos los objetivos por escaso presupuesto pues no se pudo difundir todo lo que se quer??a. Seg??n los autores, el texto es ajustado y claro y las cuarenta diapositivas conforme al mismo, el texto est?? registrado en el casete con fondo musical. La evaluaci??n es positiva y como conclusi??n lamentan que otros trabajos como este es vean afectados por la falta de presupuesto.

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Resumen tomado del autor. Incluye imágenes y material anexo

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Resumen tomado del autor

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Instructions for using the web site and the source material.