Cooperating with machines

Jacob W. Crandall; Mayada Oudah; Tennom; Fatimah Ishowo-Oloko; Sherief Abdallah; Jean-François Bonnefon; Manuel Cebrian; Azim Shariff; Michael A. Goodrich; Iyad Rahwan

doi:10.1038/s41467-017-02597-8

Nature Communications (Jan 2018)

Cooperating with machines

Jacob W. Crandall,
Mayada Oudah,
Tennom,
Fatimah Ishowo-Oloko,
Sherief Abdallah,
Jean-François Bonnefon,
Manuel Cebrian,
Azim Shariff,
Michael A. Goodrich,
Iyad Rahwan

Affiliations

Jacob W. Crandall: Computer Science Department, Brigham Young University
Mayada Oudah: Khalifa University of Science and Technology, Masdar Institute
Tennom: UVA Digital Himalaya Project, University of Virginia
Fatimah Ishowo-Oloko: Khalifa University of Science and Technology, Masdar Institute
Sherief Abdallah: British University in Dubai
Jean-François Bonnefon: Toulouse School of Economics (TSM-Research), Centre National de la Recherche Scientifique, University of Toulouse Capitole
Manuel Cebrian: The Media Lab, Massachusetts Institute of Technology
Azim Shariff: Department of Psychology and Social Behavior, University of California
Michael A. Goodrich: Computer Science Department, Brigham Young University
Iyad Rahwan: The Media Lab, Massachusetts Institute of Technology

DOI: https://doi.org/10.1038/s41467-017-02597-8
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 12

Abstract

Read online

Artificial intelligence is now superior to humans in many fully competitive games, such as Chess, Go, and Poker. Here the authors develop a machine-learning algorithm that can cooperate effectively with humans when cooperation is beneficial but nontrivial, something humans are remarkably good at.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

About the journal