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Bachelor thesis . 2019
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Bachelor thesis . 2019
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Aprendizaje por refuerzo aplicado a personajes no controlables en Minetest

descriptionPublicationkeyboard_double_arrow_right Bachelor thesis 01 Jan 2019 Spain Spanish Publisher:Universitat Politècnica de Catalunya
Authors: Romero Reviriego, Aitor;

handle: 2117/131009

Aprendizaje por refuerzo aplicado a personajes no controlables en Minetest

Abstract

En este proyecto se ha utilizado la rama de la IA llamada aprendizaje por refuerzo y intenta desarrollar agentes para el videojuego Minetest que actúen como aliados del jugador.

In this project we used the IA's field called reinforce learning and tries to develop agents in the Minetest videogame that act like player's allies.

Country
Spain
Related Organizations
Keywords

Artificial intelligence, IA, reinforce learinig, Intel·ligència artificial, Reinforcement learning, Aprenentatge per reforç, videojocs, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial, Minetest, videogames, aprenentatge per reforç, artificial inteligence, intel·ligència artificial

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average