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Defining Artificial Intelligence: a reply to Wang

Title: Defining Artificial Intelligence: a reply to Wang
Authors: Shevlin, Henry
Publisher Information: De Gruyter; //content.sciendo.com/view/journals/jagi/11/1/article-p1.xml
Publication Year: 2020
Collection: Apollo - University of Cambridge Repository
Subject Terms: 46 Information and Computing Sciences; 31 Biological Sciences; 4611 Machine Learning; Basic Behavioral and Social Science; Machine Learning and Artificial Intelligence; Behavioral and Social Science; Neurosciences; 1.2 Psychological and socioeconomic processes; Mental health
Description: Wang’s definition of Artificial Intelligence is developed via careful and thorough abstractions from human intelligence. Motivated by the goal of building a definition that will be genuinely useful for AI researchers, Wang ultimately provides an agent-centric definition that focuses on systems operating with insufficient knowledge and resources. The definition captures many key components of intelligence, but we suggest that task success could play a slightly larger role. This brings the definition closer in line with our use of the term with animals and human experts, and also further aligns the definition’s associated research framework with the subfield of deep reinforcement learning aimed at general intelligence. ; Leverhulme Trust Grant RC-2015-067.
Document Type: article in journal/newspaper
File Description: application/octet-stream; application/pdf
Language: English
Relation: https://www.repository.cam.ac.uk/handle/1810/300909
DOI: 10.17863/CAM.47983
Availability: https://www.repository.cam.ac.uk/handle/1810/300909; https://doi.org/10.17863/CAM.47983
Rights: Attribution-NoDerivatives 4.0 International ; http://creativecommons.org/licenses/by-nd/4.0/
Accession Number: edsbas.AD343A42
Database: BASE