المؤلفون: Asperti, Andrea, Cortesi, Daniele, Sovrano, Francesco

مصطلحات موضوعية: Computer Science - Machine Learning, Statistics - Machine Learning, I.2.6

الوصول الحر: http://arxiv.org/abs/1804.08685Test

المؤلفون: Asperti, Andrea, Cortesi, Daniele, Sovrano, Francesco

المساهمون: G.Nicosia, P. M. Pardalos, G.Giuffrida, R.Umeton, V.Sciacca, Asperti, Andrea, Cortesi, Daniele, Sovrano, Francesco

مصطلحات موضوعية: Deep Reinforcement Learning, Asynchronous Advantage Actor-Critic, Partially Observable Markov Decision Process, Multi-Task Learning

وصف الملف: STAMPA

العلاقة: info:eu-repo/semantics/altIdentifier/isbn/978-3-030-13708-3; info:eu-repo/semantics/altIdentifier/isbn/978-3-030-13709-0; ispartofbook:Machine Learning, Optimization, and Data Science - 4th International Conference, {LOD} 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers; Machine Learning, Optimization, and Data Science - 4th International Conference, LOD 2018; volume:11331; firstpage:264; lastpage:275; numberofpages:12; journal:LECTURE NOTES IN ARTIFICIAL INTELLIGENCE; alleditors:G.Nicosia, P. M. Pardalos, G.Giuffrida, R.Umeton, V.Sciacca; http://hdl.handle.net/11585/668591Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85063574460

الإتاحة: https://doi.org/10.1007/978-3-030-13709-0_22Test
http://hdl.handle.net/11585/668591Test

المؤلفون: Asperti, Andrea, Cortesi, Daniele, De Pieri, Carlo, Pedrini, Gianmaria, Sovrano, Francesco

المساهمون: Asperti, Andrea, Cortesi, Daniele, De Pieri, Carlo, Pedrini, Gianmaria, Sovrano, Francesco

مصطلحات موضوعية: Deep Reinforcement Learning, Dungeon, Rogue, Asynchronous Advantage Actor-Critic, Experience Replay, sparse rewards

وصف الملف: STAMPA

العلاقة: info:eu-repo/semantics/altIdentifier/wos/WOS:000544034800006; volume:12; issue:2; firstpage:177; lastpage:186; numberofpages:10; journal:IEEE TRANSACTIONS ON GAMES; https://hdl.handle.net/11585/762642Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85087546255; https://ieeexplore.ieee.org/document/8641337Test

الإتاحة: https://doi.org/10.1109/TG.2019.2899159Test
https://hdl.handle.net/11585/762642Test
https://ieeexplore.ieee.org/document/8641337Test

المؤلفون: Cortesi, Daniele

المساهمون: Asperti, Andrea

مصطلحات موضوعية: reinforcement learning,rogue,a3c,acer, Informatica [LM-DM270]

وصف الملف: application/pdf

العلاقة: http://amslaurea.unibo.it/16138/1/tesi%20Cortesi%20Daniele.pdfTest; Cortesi, Daniele (2018) Reinforcement Learning in Rogue. [Laurea magistrale], Università di Bologna, Corso di Studio in Informatica [LM-DM270]

الإتاحة: http://amslaurea.unibo.it/16138Test/
http://amslaurea.unibo.it/16138/1/tesi%20Cortesi%20Daniele.pdfTest

المؤلفون: Cortesi, Daniele

المساهمون: Bononi, Luciano, Bedogni, Luca

مصطلحات موضوعية: web service gamification marketing prossimità proximity turismo tourism, Informatica [L-DM270]

وصف الملف: application/pdf

العلاقة: http://amslaurea.unibo.it/9101/1/cortesi_daniele_tesi.pdfTest; Cortesi, Daniele (2015) Un web service per applicazioni di gamification degli itinerari turistici. [Laurea], Università di Bologna, Corso di Studio in Informatica [L-DM270]

الإتاحة: http://amslaurea.unibo.it/9101Test/
http://amslaurea.unibo.it/9101/1/cortesi_daniele_tesi.pdfTest

المؤلفون: Daniele Cortesi, Andrea Asperti, Gianmaria Pedrini, Francesco Sovrano, Carlo De Pieri

المساهمون: Asperti, Andrea, Cortesi, Daniele, De Pieri, Carlo, Pedrini, Gianmaria, Sovrano, Francesco

مصطلحات موضوعية: Generality, Point (typography), Computer science, media_common.quotation_subject, Crawling, Luck, Artificial Intelligence, Control and Systems Engineering, Asynchronous communication, Human–computer interaction, Reinforcement learning, Electrical and Electronic Engineering, Reinforcement, Deep Reinforcement Learning, Dungeon, Rogue, Asynchronous Advantage Actor-Critic, Experience Replay, sparse rewards, Video game, Software, media_common

وصف الملف: STAMPA

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59ff07379762a6ce8b70eb9144ccf288Test
https://hdl.handle.net/11585/762642Test