AI & Research · arXiv AI · publications

Visualizing the World Model in an Agent's Value Function

Source excerpt

This page presents AI and research content to help researchers, students and AI tools read, cite and verify the information.

arXiv:2610.14186v1 Announce Type: new Abstract: Could model-free reinforcement learning algorithms actually be learning a model of the environment? In this work, we apply counterfactual interventions which hold everything about a state fixed, besides a targeted change, to explore if the value function of a Proximal Policy Optimization agent forms a world model of the Crafter environment. Despite only being trained to optimize reward, we discover that the value function learns concepts such as the rules governing when a diamond is collectible, water and food having an impact on health, heuristics regarding inventory, and more. Finally, we discuss the safety implications of our visualizations and some shortcomings of current reinforcement learning agents that will prevent us from building truly advanced machine intelligence.

Your DzCademia workshop

Check a publication method or promise

A video or journal-finding tool can shortlist titles, not guarantee acceptance. Check identity, scope, author instructions and possible fees at official sources. Do not choose solely on speed promises or one indicator.

A practical exercise

Compare two journals against your research question: fit, article types, instructions and verified terms. Keep unknowns as questions rather than assumptions.

Record reference points

Topic: Visualizing the World Model in an Agent's Value Function
Source website: arxiv.org
Publication date at source: 2026-10-15
Collection date on DzCademia: 2026-10-15

My preparation plan

An indicative personal list, separate from official documents or requirements. Checkmarks stay on this device; no account needed.

Identify the journal and official site.Read the scope and sample papers.Check instructions and possible charges.Reject unsupported publication guarantees.Prepare an original, compliant manuscript.

0 / 5 steps checked

Read the source

DzCademia advice and exercises are separate from the source summary and requirements. This structured aid uses automated assistance and is neither scientific validation nor a selection promise. Source consulted on 2026-10-28.

intelligence artificielle politique IA

View the original source

Official or original source: arXiv AI. Always check the details against the primary source.

Back to AI & Research

Visualizing the World Model in an Agent's Value Function

Check a publication method or promise

A practical exercise

Comment with Google

Your browsing, your choices