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Related Experiment Video

Updated: May 15, 2026

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Published on: April 18, 2017

Goals and the structure of experience.

Nadav Amir¹, Stas Tiomkin², Angela Langdon³

¹Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|May 14, 2026

Summary

This study introduces a new computational framework for purposeful behavior in cognitive agents. It proposes that descriptive and prescriptive world models emerge together from an agent's goals and experiences, offering a unified view of intelligence.

Keywords:

goals learning and decision-making state representation

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Area of Science:

Cognitive Science
Artificial Intelligence
Computational Neuroscience

Background:

Purposeful behavior is key to natural and artificial intelligence.
Current models often separate descriptive (state representation) and prescriptive (reward function) world model components.
An alternative is that these aspects co-emerge from an agent's goals.

Purpose of the Study:

To present a computational framework where descriptive and prescriptive world model aspects co-emerge.
To introduce the concept of 'telic states' based on Buddhist epistemology.
To offer a unified account of purposeful behavior.

Main Methods:

Developed a computational framework for goal-directed state representation.
Defined 'telic states' as classes of goal-equivalent experience distributions.
Utilized agent-environment interaction sequences (experiences).

Main Results:

Demonstrated how descriptive and prescriptive world model aspects can co-emerge.
Showcased 'telic states' as a parsimonious model for goal-directed learning.
Linked goal-directed learning to statistical divergence between policies and desired experiences.

Conclusions:

The proposed framework offers a novel perspective on world models and purposeful behavior.
Telic states provide a unified account across behavioral, phenomenological, and neural dimensions.
This approach has potential applications in understanding intelligence across diverse substrates.