Childhood as a solution to explore–exploit tensions

Philosophical Transactions of the Royal Society B Biological Sciences, Journal Year: 2020, Volume and Issue: 375(1803), P. 20190502 - 20190502

Published: May 31, 2020

I argue that the evolution of our life history, with its distinctively long, protected human childhood, allows an early period broad hypothesis search and exploration, before demands goal-directed exploitation set in. This cognitive profile is also found in other animals associated behaviours such as neophilia play. relate this developmental pattern to computational ideas about explore-exploit trade-offs, sampling, neuroscience findings. present several lines empirical evidence suggesting young learners are highly exploratory, both terms their for external information through spaces. In fact, they sometimes more exploratory than older adults. article part theme issue 'Life history learning: how caregiving old age shape cognition culture humans animals'.

Language: Английский

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The algorithmic architecture of exploration in the human brain

Current Opinion in Neurobiology, Journal Year: 2018, Volume and Issue: 55, P. 7 - 14

Published: Dec. 6, 2018

Language: Английский

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Balancing exploration and exploitation with information and randomization

Current Opinion in Behavioral Sciences, Journal Year: 2020, Volume and Issue: 38, P. 49 - 56

Published: Nov. 6, 2020

Language: Английский

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When Is More Uncertainty Better? A Model of Uncertainty Regulation and Effectiveness

Academy of Management Review, Journal Year: 2020, Volume and Issue: 45(4), P. 745 - 765

Published: March 3, 2020

Across all fields of management research, uncertainty is largely considered an aversive state that people and organizations cope with unwillingly generally aim to avoid. However, theories based on principles reduction overlook opportunities arising from creation. Building recent research in management, cognition, neuroscience, we expand current conceptualizations by introducing a model regulation where individuals employ opening closing behaviors achieve alignment between preferred experienced levels exogenous requirements for effectiveness. We derive propositions work performance extend existing concepts adaptation uncertain environments include deliberate creation expansive agency. discuss implications dynamic models agentic goal striving, organizational support individuals' regulation, extensions team- organization-level phenomena.

Language: Английский

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The development of human causal learning and reasoning

Nature Reviews Psychology, Journal Year: 2024, Volume and Issue: 3(5), P. 319 - 339

Published: April 26, 2024

Language: Английский

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Dynamic computational phenotyping of human cognition

Nature Human Behaviour, Journal Year: 2024, Volume and Issue: 8(5), P. 917 - 931

Published: Feb. 8, 2024

Abstract Computational phenotyping has emerged as a powerful tool for characterizing individual variability across variety of cognitive domains. An individual’s computational phenotype is defined set mechanistically interpretable parameters obtained from fitting models to behavioural data. However, the interpretation these hinges critically on their psychometric properties, which are rarely studied. To identify sources governing temporal phenotype, we carried out 12-week longitudinal study using battery seven tasks that measure aspects human learning, memory, perception and decision making. examine influence state effects, each week, participants provided reports tracking mood, habits daily activities. We developed dynamic framework, allowed us tease apart time-varying effects practice internal states such affective valence arousal. Our results show many dimensions covary with factors, indicating what appears be unreliability may reflect previously unmeasured structure. These support fundamentally understanding within an individual.

Language: Английский

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Children are more exploratory and learn more than adults in an approach-avoid task

Cognition, Journal Year: 2021, Volume and Issue: 218, P. 104940 - 104940

Published: Oct. 27, 2021

Intuitively, children appear to be more exploratory than adults, and this exploration seems help learn,. However, there have been few clear tests of these ideas. We test whether learning change across development using a task that presents "learning trap." In task, exploitation-maximizing immediate reward avoiding costs-may lead the learner draw incorrect conclusions, while may better but costly. Studies 1, 2, 3 we find preschoolers early school-aged explore adults learn true structure environment better. Study demonstrates even though they, like predict will costly, it shows are correlated. 4 children's adults' depends on evidence they generate during exploration: exposed adult-like child-like children. Together, studies support idea increased influences learning.

Language: Английский

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Explanation-seeking curiosity in childhood

Current Opinion in Behavioral Sciences, Journal Year: 2020, Volume and Issue: 35, P. 14 - 20

Published: July 7, 2020

Children are known for asking 'why?' — a query motivated by their desire explanations. Research suggests that explanation-seeking curiosity (ESC) is triggered first-person cues (such as novelty or surprise), third-person knowledgeable adults' surprise question), and future-oriented expectations about information gain future value). Once triggered, ESC satisfied an adequate explanation, typically obtained through causal intervention question asking, both of which change in efficiency over development. important driver children's learning because it combines the power active intrinsic motivation with value explanatory content, can reveal unobservable structure world to support generalizable knowledge.

Language: Английский

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Disentangling the systems contributing to changes in learning during adolescence

Developmental Cognitive Neuroscience, Journal Year: 2019, Volume and Issue: 41, P. 100732 - 100732

Published: Nov. 14, 2019

Multiple neurocognitive systems contribute simultaneously to learning. For example, dopamine and basal ganglia (BG) are thought support reinforcement learning (RL) by incrementally updating the value of choices, while prefrontal cortex (PFC) contributes different computations, such as actively maintaining precise information in working memory (WM). It is commonly that WM PFC show more protracted development than RL BG systems, yet their contributions rarely assessed tandem. Here, we used a simple task test how changes across adolescence. We tested 187 subjects ages 8 17 53 adults (25-30). Participants learned stimulus-action associations from feedback; load was varied be within or exceed capacity. age 8-12 slower participants 13-17, were sensitive load. computational modeling estimate subjects' use processes. Surprisingly, found during development. rate increased with until 18 parameters showed subtle, gender- puberty-dependent early These results can inform education intervention strategies based on developmental science

Language: Английский

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Development of directed and random exploration in children

Developmental Science, Journal Year: 2021, Volume and Issue: 24(4)

Published: Feb. 5, 2021

Are young children just random explorers who learn serendipitously? Or are even guided by uncertainty-directed sampling, seeking to explore in a systematic fashion? We study how between the ages of 4 and 9 search an explore-exploit task with spatially correlated rewards, where exhaustive exploration is infeasible not all options can be experienced. By combining behavioral data computational model that decomposes into similarity-based generalization, exploration, we map out developmental trajectories generalization exploration. The show strong differences children's capability exploit environmental structure, performance adaptiveness sampling decisions increasing age. Through model-based analyses, disentangle different forms finding signature both amount strongly decreases as get older, supporting notion "cooling off" process modulates randomness sampling. However, at youngest age range, do solely rely on Even begins taper off, actively high uncertainty goal-directed fashion, using inductive inferences generalize their experience novel options. Our findings provide critical insights principles underlying trajectory learning

Language: Английский

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