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In 1975 distributed artificial intelligence emerged as a subfield of artificial intelligence that dealt with interactions of intelligent agents. [2] Distributed artificial intelligence systems were conceived as a group of intelligent entities, called agents, that interacted by cooperation, by coexistence or by competition.
The Distributed Artificial Intelligence Research Institute (or DAIR Institute) is a research institute founded by Timnit Gebru in December 2021. [1] [2] The institute announced itself as "an independent, community-rooted institute set to counter Big Tech’s pervasive influence on the research, development and deployment of AI." [3]
Advances in Distributed Computing and Artificial Intelligence Journal is a peer-reviewed scientific journal covering the fields of artificial intelligence and distributed computing and applying these techniques in areas like machine learning, electronic commerce, generative AI, the Internet of Things, smart grids, etc.
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
For contributions to distributed artificial intelligence, multiagent systems, and real-time intelligent control. 2016: Schahram Dustdar: For contributions to elastic computing for cloud applications 2008: Nikil Dutt: For contributions to architecture description languages for the design and exploration of customized processors 2020: Ashutosh Dutta
Pages in category "Distributed artificial intelligence" The following 4 pages are in this category, out of 4 total. This list may not reflect recent changes. ...
Artificial intelligence engineering (AI engineering) is a technical discipline that focuses on the design, development, and deployment of AI systems. AI engineering involves applying engineering principles and methodologies to create scalable, efficient, and reliable AI-based solutions.
Artificial intelligence is used in astronomy to analyze increasing amounts of available data [159] [160] and applications, mainly for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights" for example for discovering exoplanets, forecasting solar activity, and distinguishing ...