An Approach to Unification of Application Programming Interfaces of Gaming Platforms for Artificial Intelligence

Ponomareva, O.; Vesnin, D.; Vesnina, A.

doi:10.1109/USBEREIT.2019.8736615

Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/101736

Title:	An Approach to Unification of Application Programming Interfaces of Gaming Platforms for Artificial Intelligence
Authors:	Ponomareva, O. Vesnin, D. Vesnina, A.
Issue Date:	2019
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Citation:	Ponomareva O. An Approach to Unification of Application Programming Interfaces of Gaming Platforms for Artificial Intelligence / O. Ponomareva, D. Vesnin, A. Vesnina. — DOI 10.1109/USBEREIT.2019.8736615 // Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019. — 2019. — P. 292-294. — 8736615.
Abstract:	This paper explores several existing gaming platforms for training and testing artificial intelligence, their application programming interfaces analyzed in order to discover potential complications of porting intellectual systems between them. We present an approach to unification of programming interfaces in order to overcome these complications. Advantages and potential side effects of this approach are described. © 2019 IEEE.
Keywords:	APPLICATION PROGRAMMING INTERFACE ARTIFICIAL INTELLIGENCE DEEP LEARNING MACHINE LEARNING REINFORCEMENT LEARNING VIDEO GAMES APPLICATION PROGRAMMING INTERFACES (API) ARTIFICIAL INTELLIGENCE BIOMEDICAL ENGINEERING DEEP LEARNING LEARNING SYSTEMS MACHINE LEARNING REINFORCEMENT LEARNING INTELLECTUAL SYSTEMS PROGRAMMING INTERFACE SIDE EFFECT TRAINING AND TESTING VIDEO GAME COMPUTER SYSTEMS PROGRAMMING
URI:	http://elar.urfu.ru/handle/10995/101736
Access:	info:eu-repo/semantics/openAccess
SCOPUS ID:	85068605250
WOS ID:	000481645800076
PURE ID:	8e125584-9aa3-4e82-9a19-5a99883e3b0c 10284056
ISBN:	9781538683644
DOI:	10.1109/USBEREIT.2019.8736615
Appears in Collections:	Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

Files in This Item:

File	Description	Size	Format
2-s2.0-85068605250.pdf		393,33 kB	Adobe PDF	View/Open

Show full item record