Aprendizaje por refuerzo aplicado a los videojuegos cooperativos

Name: Aprendizaje por refuerzo aplicado a los videojuegos cooperativos
Creator: Alcocer Soto, Daniel
Keywords: xarxes neuronals, cooperativity, Videojocs, RL, video games, NN, neural networks, aprenentatge automàtic, Neural networks (Computer science), Video games

Alcocer Soto, Daniel

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Bachelor thesis . 2018

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Recolector de Ciencia Abierta, RECOLECTA

Bachelor thesis . 2018

Data sources: Recolector de Ciencia Abierta, RECOLECTA

Recolector de Ciencia Abierta, RECOLECTA

Bachelor thesis . 2018

Data sources: Recolector de Ciencia Abierta, RECOLECTA

Aprendizaje por refuerzo aplicado a los videojuegos cooperativos

descriptionPublicationkeyboard_double_arrow_right Bachelor thesis 01 Jan 2018 Spain Publisher:Universitat Politècnica de Catalunya

Authors: Alcocer Soto, Daniel;

handle: 2117/122583

Aprendizaje por refuerzo aplicado a los videojuegos cooperativos

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Abstract

Se ha desarrollado un algoritmo que combina el uso de redes neuronales con el algoritmo Q-learning para aprender a jugar con la ayuda de un jugador humano y aprender a cooperar con él para ganar en un videojuego basado en los combates dobles de Pokémon, el cual ha sido creado des de cero.

An algorithm has been developed that combines the use of neural networks with the Q-learning algorithm to learn to play with the help of a human player and to learn to cooperate with him to win a videogame based on Pokémon's double combat, which has been developed from scratch.

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Spain

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Keywords

xarxes neuronals, cooperativity, Videojocs, RL, video games, NN, neural networks, aprenentatge automàtic, Neural networks (Computer science), Video games, cooperativitat, machine learning, :Informàtica [Àrees temàtiques de la UPC], Machine learning, Reinforcement learning, Aprenentatge automàtic, Aprenentatge per reforç, videojocs, Xarxes neuronals (Informàtica), Àrees temàtiques de la UPC::Informàtica, aprenentatge per reforç

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