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n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications

This paper provides a conceptual foundation for stochastic duels and contains a further study of the game models based on the theory of stochastic duels. Some other combat assessment techniques are looked upon briefly; a modern outlook on the applications of the theory through video games is provide...

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Autores principales: Gupta, Manik, Sharma, Bhisham, Tripathi, Akarsh, Singh, Shashank, Bhola, Abhishek, Singh, Rajani, Dwivedi, Ashutosh Dhar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952783/
https://www.ncbi.nlm.nih.gov/pubmed/35336591
http://dx.doi.org/10.3390/s22062422
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author Gupta, Manik
Sharma, Bhisham
Tripathi, Akarsh
Singh, Shashank
Bhola, Abhishek
Singh, Rajani
Dwivedi, Ashutosh Dhar
author_facet Gupta, Manik
Sharma, Bhisham
Tripathi, Akarsh
Singh, Shashank
Bhola, Abhishek
Singh, Rajani
Dwivedi, Ashutosh Dhar
author_sort Gupta, Manik
collection PubMed
description This paper provides a conceptual foundation for stochastic duels and contains a further study of the game models based on the theory of stochastic duels. Some other combat assessment techniques are looked upon briefly; a modern outlook on the applications of the theory through video games is provided; and the possibility of usage of data generated by popular shooter-type video games is discussed. Impactful works to date are carefully chosen; a timeline of the developments in the theory of stochastic duels is provided; and a brief literature review for the same is conducted, enabling readers to have a broad outlook at the theory of stochastic duels. A new evaluation model is introduced in order to match realistic scenarios. Improvements are suggested and, additionally, a trust mechanism is introduced to identify the intent of a player in order to make the model a better fit for realistic modern problems. The concept of teaming of players is also considered in the proposed mode. A deep-learning model is developed and trained on data generated by video games to support the results of the proposed model. The proposed model is compared to previously published models in a brief comparison study. Contrary to the conventional stochastic duel game combat model, this new proposed model deals with pair-wise duels throughout the game duration. This model is explained in detail, and practical applications of it in the context of the real world are also discussed. The approach toward solving modern-day problems through the use of game theory is presented in this paper, and hence, this paper acts as a foundation for researchers looking forward to an innovation with game theory.
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spelling pubmed-89527832022-03-26 n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications Gupta, Manik Sharma, Bhisham Tripathi, Akarsh Singh, Shashank Bhola, Abhishek Singh, Rajani Dwivedi, Ashutosh Dhar Sensors (Basel) Article This paper provides a conceptual foundation for stochastic duels and contains a further study of the game models based on the theory of stochastic duels. Some other combat assessment techniques are looked upon briefly; a modern outlook on the applications of the theory through video games is provided; and the possibility of usage of data generated by popular shooter-type video games is discussed. Impactful works to date are carefully chosen; a timeline of the developments in the theory of stochastic duels is provided; and a brief literature review for the same is conducted, enabling readers to have a broad outlook at the theory of stochastic duels. A new evaluation model is introduced in order to match realistic scenarios. Improvements are suggested and, additionally, a trust mechanism is introduced to identify the intent of a player in order to make the model a better fit for realistic modern problems. The concept of teaming of players is also considered in the proposed mode. A deep-learning model is developed and trained on data generated by video games to support the results of the proposed model. The proposed model is compared to previously published models in a brief comparison study. Contrary to the conventional stochastic duel game combat model, this new proposed model deals with pair-wise duels throughout the game duration. This model is explained in detail, and practical applications of it in the context of the real world are also discussed. The approach toward solving modern-day problems through the use of game theory is presented in this paper, and hence, this paper acts as a foundation for researchers looking forward to an innovation with game theory. MDPI 2022-03-21 /pmc/articles/PMC8952783/ /pubmed/35336591 http://dx.doi.org/10.3390/s22062422 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gupta, Manik
Sharma, Bhisham
Tripathi, Akarsh
Singh, Shashank
Bhola, Abhishek
Singh, Rajani
Dwivedi, Ashutosh Dhar
n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications
title n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications
title_full n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications
title_fullStr n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications
title_full_unstemmed n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications
title_short n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications
title_sort n-player stochastic duel game model with applied deep learning and its modern implications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952783/
https://www.ncbi.nlm.nih.gov/pubmed/35336591
http://dx.doi.org/10.3390/s22062422
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