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Reasoning-Learning Systems Based on Non-Axiomatic Reasoning System Theory

Author:

Year: 2022
Venue: Proceedings of Machine Learning Research, International Workshop on Self-Supervised Learning
Links: PDF

Summary

Compares a reasoning-learning approach based on Non-Axiomatic Reasoning System theory with common reinforcement-learning techniques. The paper frames ONA/NARS as a system for learning from experience under uncertainty while taking explicit background knowledge into account.

Relevance to Hyperon

This paper supports MeTTa-NARS Deep Dive by documenting the reasoning-learning side of the NARS/ONA tradition, especially the relationship between uncertainty reasoning, practical reasoning, and procedure learning.

Key References

• RawData source
• MeTTa-NARS Deep Dive