Evidence map›Paper›PMID 39416795›Full record

ArticleFrontiers in robotics and AI2024

Towards a computational model for higher orders of Theory of Mind in social agents.

Federico Tavella, Federico Manzi, Samuele Vinanzi, Cinzia Di Dio, Davide Massaro, Angelo Cangelosi, Antonella Marchetti

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Federico TavellaManchester Centre for Robotics and AI, The University of Manchester, Manchester, United Kingdom.
Federico ManziResearch Center on Theory of Mind and Social Competence in the Lifespan (CeRiToM), Università Cattolica del Sacro Cuore, Milan, Italy.
Samuele VinanziDepartment of Computing, Sheffield Hallam University, Sheffield, United Kingdom.
Cinzia Di DioResearch Center on Theory of Mind and Social Competence in the Lifespan (CeRiToM), Università Cattolica del Sacro Cuore, Milan, Italy.
Davide MassaroResearch Center on Theory of Mind and Social Competence in the Lifespan (CeRiToM), Università Cattolica del Sacro Cuore, Milan, Italy.
Angelo CangelosiManchester Centre for Robotics and AI, The University of Manchester, Manchester, United Kingdom.
Antonella MarchettiResearch Center on Theory of Mind and Social Competence in the Lifespan (CeRiToM), Università Cattolica del Sacro Cuore, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective communication between humans and machines requires artificial tools to adopt a human-like social perspective. The Theory of Mind (ToM) enables understanding and predicting mental states and behaviours, crucial for social interactions from childhood through adulthood. Artificial agents with ToM skills can better coordinate actions, such as in warehouses or healthcare. Incorporating ToM in AI systems can revolutionise our interactions with intelligent machines. This proposal emphasises the current focus on first-order ToM models in the literature and investigates the potential of creating a computational model for higher-order ToM.

Indexed as

artificial intelligencecomputational modellingperspective takingsocial agentstheory of mind

Identifiers

PMID39416795
PMCPMC11479858

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.