Evidence map›Paper›PMID 34721565›Full record

ArticleComputational intelligence and neuroscience2021

Affective Episodic Memory System for Virtual Creatures: The First Step of Emotion-Oriented Memory.

Luis Martin, Jonathan H Rosales, Karina Jaime, Felix Ramos

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Luis MartinDepartment of Computer Science, Center for Research and Advanced Studies of the National Polytechnic Institute, Zapopan 45019, Mexico.ORCID https://orcid.org/0000-0002-4864-0635
Jonathan H RosalesFaculty of Science and Technology, Autonomous University of Guadalajara, Zapopan 45129, Mexico.ORCID https://orcid.org/0000-0002-4261-0726
Karina JaimeDepartment of Computer Science, Center for Research and Advanced Studies of the National Polytechnic Institute, Zapopan 45019, Mexico.ORCID https://orcid.org/0000-0001-8086-4295
Felix RamosDepartment of Computer Science, Center for Research and Advanced Studies of the National Polytechnic Institute, Zapopan 45019, Mexico.ORCID https://orcid.org/0000-0002-0116-7203

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Episodic memory and emotions are considered essential functions in human cognition. Both allow us to acquire new knowledge from the environment, ranging from the objects around us to how we feel towards them. These qualities make them crucial functions for systems trying to create human-like behaviour. In the field of cognitive architectures (CAs), there are multiple studies covering memory and emotions. However, most of them treat these subjects in an isolated manner, considering emotions only as a reward signal unrelated to a retrieved experience. To address this lack of direct interaction, we propose a computational model that covers the common processes that are related to memory and emotions. Specifically, this proposal focuses on affective evaluations of episodic memories. Neurosciences and psychology are the bases of this model. That is, the model's components and the processes that they carry out on the information they receive are designed based on evidence from these cognitive sciences. The proposed model is a part of Cuáyóllótl, a cognitive architecture for cybernetic entities such as virtual creatures and robots. Case studies validate our proposal. They show the relevance of the integration of emotions and memory in a virtual creature. The virtual creature endowed with our emotional episodic model improves its learning and modifies its behaviour according to planning and decision-making processes.

Indexed as

Memory, EpisodicCognitionEmotionsHumansLearning

Identifiers

PMID34721565
PMCPMC8550857

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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.