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Related Experiment Video

Updated: Jan 25, 2026

Study Design for Navigated Repetitive Transcranial Magnetic Stimulation for Speech Cortical Mapping

Study Design for Navigated Repetitive Transcranial Magnetic Stimulation for Speech Cortical Mapping

Published on: March 24, 2023

Composing egocentric and allocentric maps for flexible navigation.

Daniel Shani^1,2,3, Peter Dayan^1,2

¹Max Planck Institute for Biological Cybernetics, Tübingen, Germany.

Plos Computational Biology

|January 23, 2026

Summary

This summary is machine-generated.

This study introduces egocentric successor representations (SRs) combined with allocentric SRs for navigation. This integration enhances an agent's ability to learn policies and adapt to new environments efficiently.

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Area of Science:

Cognitive Science
Neuroscience
Artificial Intelligence

Background:

Egocentric representations are traditionally limited to simple behaviors.
Egocentric representations may exist in the hippocampal formation.
Modern navigation methods have not fully integrated egocentric representations.

Purpose of the Study:

Investigate egocentric successor representations (SRs).
Combine egocentric SRs with allocentric representations for navigation.
Develop a reinforcement learning agent for complex 2D environments.

Main Methods:

Built a reinforcement learning agent.
Combined egocentric and allocentric SRs.
Trained the agent in complex 2D environments.

Main Results:

The agent learned generalizable egocentric and allocentric value functions.
Additive composition of representations enabled efficient policy learning.
The agent adapted quickly to new environments.

Conclusions:

Egocentric relational structure is beneficial for navigation.
Cognitive maps can be composed from multiple simple maps.
This approach offers a new perspective on cognitive map composition.