The Mental Representation of Human Action

Cognitive Science, Forthcoming

82 Pages Posted: 3 Mar 2018 Last revised: 8 Mar 2018

Sydney Levine

Massachusetts Institute of Technology (MIT)

Alan Leslie

Rutgers University, New Brunswick

John Mikhail

Georgetown University Law Center

Date Written: March 2, 2018

Abstract

Various theories of moral cognition posit that moral intuitions can be understood as the output of a computational process performed over structured mental representations of human action. We propose that action plan diagrams — “act trees” — can be a useful tool for theorists to succinctly and clearly present their hypotheses about the information contained in these representations. We then develop a methodology for using a series of linguistic probes to test the theories embodied in the act trees. In Study 1, we validate the method by testing a specific hypothesis (diagrammed by act trees) about how subjects are representing two classic moral dilemmas and finding that the data support the hypothesis. In Studies 2-4, we explore possible explanations for discrete and surprising findings that our hypothesis did not predict. In Study 5, we apply the method to a less well-studied case and show how new experiments generated by our method can be used to settle debates about how actions are mentally represented. In Study 6, we argue that our method captures the mental representation of human action better than an alternative approach. A brief conclusion suggests that act trees can be profitably used in various fields interested in complex representations of human action, including law, philosophy, psychology, neuroscience, computer science, robotics and artificial intelligence.

Keywords: Moral Judgment, Act Trees, Moral Grammar, Human Action, Intention

Suggested Citation

Levine, Sydney and Leslie, Alan and Mikhail, John, The Mental Representation of Human Action (March 2, 2018). Cognitive Science, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3133359

Sydney Levine

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Alan Leslie

Rutgers University, New Brunswick ( email )

New Brunswick, NJ
United States

John Mikhail (Contact Author)

Georgetown University Law Center ( email )

600 New Jersey Avenue, NW
Washington, DC 20001
United States
202-662-9392 (Phone)
202-662-9409 (Fax)

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