Rethinking the Simulation Theory

This paper revisits the Simulation Theory (ST) as a framework for understanding human social cognition, challenging traditional ‘theory of mind’ or ‘folk psychology’ approaches. While these theory-based models posit that humans use an implicit body of knowledge to interpret and predict others’ behavior, ST emphasizes the use of mental simulation, leveraging the brain’s existing mechanisms for planning and prediction. By employing a predictive coding strategy, the brain minimizes cognitive load, interpreting others' actions through ‘inverse planning’ – a process that reuses one’s own action planning system to hypothesize the goals and intentions of others. The concept of agent-neutral coding is introduced, proposing that inputs for self and others are initially shared, reducing the need for explicit mental state attributions. This approach not only economizes cognitive resources but aligns with evolutionary perspectives on human social interaction in small, cohesive groups. In addition, the paper explores the role of perspective-taking and error correction in adapting shared mental representation. This reevaluation of ST underscores its efficiency and adaptability, offering a streamlined alternative to theory-based accounts of social cognition.

Authors

Institutions

Publication Details

Journal
JOLMA
Published
2025-09-01
DOI
https://doi.org/10.30687/jolma/2723-9640/2025/01/003
Primary Topic
Complex Systems and Decision Making
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rethinking the Simulation Theory

Robert M. Gordon
JOLMA
Complex Systems and Decision Making
article

Rethinking the Simulation Theory

Robert M. Gordon
article en

Abstract

This paper revisits the Simulation Theory (ST) as a framework for understanding human social cognition, challenging traditional ‘theory of mind’ or ‘folk psychology’ approaches. While these theory-based models posit that humans use an implicit body of knowledge to interpret and predict others’ behavior, ST emphasizes the use of mental simulation, leveraging the brain’s existing mechanisms for planning and prediction. By employing a predictive coding strategy, the brain minimizes cognitive load, interpreting others' actions through ‘inverse planning’ – a process that reuses one’s own action planning system to hypothesize the goals and intentions of others. The concept of agent-neutral coding is introduced, proposing that inputs for self and others are initially shared, reducing the need for explicit mental state attributions. This approach not only economizes cognitive resources but aligns with evolutionary perspectives on human social interaction in small, cohesive groups. In addition, the paper explores the role of perspective-taking and error correction in adapting shared mental representation. This reevaluation of ST underscores its efficiency and adaptability, offering a streamlined alternative to theory-based accounts of social cognition.

JOLMA(1)
University of Missouri–St. Louis (US)
Openalex Percentile: Top 73%
Complex Systems and Decision Making
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.