Quantum mechanics

Valence (chemistry)

Artifact (error)

Cognitive psychology

Neuroscience

Social psychology

Variety (cybernetics)

Cognition

Computer science

Surprise

PsycINFO

Cognitive science

Physics

Theory of mind

Psychology

Salience (neuroscience)

Political science

Artificial intelligence

MEDLINE

Social cognition

Psychological Review

In this article, we argue that a predictive processing framework (PP) may provide elements for a proximate model of play in children and adults.We propose that play is a behavior in which the agent, in contexts of freedom from the demands of certain competing cognitive systems, deliberately seeks out or creates surprising situations that gravitate toward sweet-spots of relative complexity with the goal of resolving surprise.We further propose that play is experientially associated with a feel-good quality because the agent is reducing significant levels of prediction error (i.e., surprise) faster than expected.We argue that this framework can unify a range of well-established findings in play and developmental research that highlights the role of play in learning, and that casts children as Bayesian learners.The theory integrates the role of positive valence in play (i.e., explaining why play is fun); and what it is to be in a playful mood.Central to the account is the idea that playful agents may create and establish an environment tailored to the generation and further resolution of surprise and uncertainty.Play emerges here as a variety of niche construction where the organism modulates its physical and social environment in order to maximize the productive potential of surprise.

Play in predictive minds: A cognitive theory of play.