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Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

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Complex behavior from intrinsic motivation to occupy future action-state path space.

Jorge Ramírez-Ruiz¹, Dmytro Grytskyy², Chiara Mastrogiuseppe²

¹Center for Brain and Cognition, Departament d'Enginyeria i Escola d'Enginyeria, Universitat Pompeu Fabra, Barcelona, Spain. jorgeerrz@gmail.com.

Nature Communications

|July 29, 2024

Summary

This study proposes a new theory of behavior: agents aim to maximize occupancy of future action-state paths, not rewards. This "maximum occupancy principle" explains curiosity and complex behaviors like dancing and altruism without reward maximization.

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Area of Science:

Behavioral science
Computational neuroscience
Reinforcement learning

Background:

Traditional behavior theories focus on reward maximization.
Animal behavior often appears reward-free and curiosity-driven.

Purpose of the Study:

To propose a novel theory of behavior based on maximizing future path occupancy.
To explain intrinsic motivation and complex behaviors without reward maximization.

Main Methods:

Introduced the maximum occupancy principle.
Utilized action-state path entropy as the key measure.
Developed analytical expressions and a value iteration algorithm.

Main Results:

Demonstrated that action-state path entropy is consistent with additivity.
Showcased complex behaviors (dancing, hide-and-seek, altruism) emerging from path occupancy maximization.
Proved convergence of the value iteration algorithm.

Conclusions:

Behavioral goals emerge from the intrinsic motivation to occupy future action-state paths.
The maximum occupancy principle offers a unified framework for understanding goal-directedness and variability.
This theory provides a new perspective on intrinsic motivation in artificial and biological agents.