Toward an automated science of the mind

arXiv:2603.20988 · cs.AI, q-bio.NC · Submitted 2026-03-22 · Read on arXiv

cs.AI, q-bio.NC

Submitted: 2026-03-22

Updated: 2026-09-21

License: http://creativecommons.org/licenses/by/4.0/

The gist: Artificial Intelligence is starting to automate scientific discovery, raising the prospect of an automated science of the mind.

Terminology

• Foundation Model — 7× in this paper · explained in 3 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Active Learning — 1× in this paper · explained in 6 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Hybrid System — 1× in this paper · explained in 2 episodes
• Information Gain — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Parsimony — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes

Abstract

Sources

• The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
• Procedural generation of meta-reinforcement learning tasks
• Turning large language models into cognitive models
• Program Synthesis with Large Language Models
• AlphaEvolve: A coding agent for scientific and algorithmic discovery
• The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

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