AXIOM: Mastering Arcade Games in Minutes with Active Inference and Structure Learning

2025-06-24 · Source: Research Blog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Gaming & Interactive Media · Depth: Advanced, quick

Summary

AXIOM is a novel active inference agent designed to master arcade games with minimal experience, mirroring human learning efficiency. It achieves this by starting with strong hypotheses about world organization, learning from single examples, and generalizing insights without extensive replay. AXIOM balances exploration for information gain with exploitation of rewarding actions, facilitating rapid discovery of relevant environmental structure. This approach allows the agent to quickly adapt to new game dynamics and achieve proficiency in minutes, demonstrating a significant advancement in sample-efficient reinforcement learning by integrating active inference and structure learning.

Key takeaway

For AI researchers developing sample-efficient agents, consider integrating active inference with structure learning. Your models could achieve human-like learning speeds in complex environments, significantly reducing the data and computational resources typically required for training. This approach offers a path to more adaptable and generalizable AI systems.

Key insights

AXIOM uses active inference and structure learning for sample-efficient arcade game mastery, mimicking human learning.

Principles

• Efficient learning starts with strong world hypotheses.
• Balance exploration and exploitation for rapid discovery.

Method

AXIOM employs active inference to generate hypotheses and learn environmental structure, balancing curiosity-driven exploration with exploitation of known rewards to master complex tasks quickly.

In practice

• Apply strong prior hypotheses in RL agents.
• Integrate active inference for sample efficiency.

Topics

• Active Inference
• Structure Learning
• Arcade Games
• Sample-Efficient Learning
• Exploration-Exploitation

Best for: AI Researcher, AI Scientist, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Research Blog.