Organisms need to constantly balance the competing demands of gathering information and using previously acquired information to obtain rewarding outcomes (i.e., the "exploration-exploitation" dilemma). Exploration is critical to obtain information to discover how the world works, which should be particularly important for young children. While studies have shown that young children explore in response to surprising events, little is known about how they balance exploration and exploitation across multiple decisions or about how this process changes with development. In this study, we compare decision-making patterns of children and adults and evaluate the relative influences of reward seeking, random exploration, and systematic switching (which approximates uncertainty-directed exploration). In a second experiment, we directly test the effect of uncertainty on children's choices. Influential models of decision-making generally describe systematic exploration as a computationally refined capacity that relies on top-down cognitive control. We demonstrate that (a) systematic patterns dominate young children's behavior (facilitating exploration), despite protracted development of cognitive control; and (b) that uncertainty plays a major, but complicated, role in determining children's choices. We conclude that while young children's immature top-down control should hinder adult-like systematic exploration, other mechanisms may pick up the slack, facilitating broad information gathering in a systematic fashion to build a foundation of knowledge for use later in life.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867663PMC
http://dx.doi.org/10.1111/desc.13026DOI Listing

Publication Analysis

Top Keywords

systematic exploration
12
young children's
12
children's choices
12
dominate young
8
young children
8
cognitive control
8
exploration
7
systematic
6
young
5
children's
5

Similar Publications

Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.

Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.

Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.

View Article and Find Full Text PDF

Exploring the Credibility of Large Language Models for Mental Health Support: Protocol for a Scoping Review.

JMIR Res Protoc

January 2025

Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.

Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.

View Article and Find Full Text PDF

Background: Lifestyle interventions have been acknowledged as effective strategies for preventing type 2 diabetes mellitus (T2DM). However, the accessibility of conventional face-to-face interventions is often limited. Digital health intervention has been suggested as a potential solution to overcome the limitation.

View Article and Find Full Text PDF

Background: Although substantial progress has been made in establishing evidence-based psychosocial clinical interventions and implementation strategies for mental health, translating research into practice-particularly in more accessible, community settings-has been slow.

Objective: This protocol outlines the renewal of the National Institute of Mental Health-funded University of Washington Advanced Laboratories for Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center, which draws from human-centered design (HCD) and implementation science to improve clinical interventions and implementation strategies. The Center's second round of funding (2023-2028) focuses on using the Discover, Design and Build, and Test (DDBT) framework to address 3 priority clinical intervention and implementation strategy mechanisms (ie, usability, engagement, and appropriateness), which we identified as challenges to implementation and scalability during the first iteration of the center.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!