NON-AXIOMATIC LOGIC (2ND ED)

This book provides a comprehensive, up-to-date, and rigorously detailed introduction to Non-Axiomatic Logic (NAL), a groundbreaking framework for adaptive systems operating under conditions of insufficient knowledge and resources. Designed according to the principles of human cognition, NAL serves as a cornerstone for advancing general-purpose Artificial Intelligence while addressing many topics in logic, psychology, linguistics, philosophy, and computer science.

Now fully expanded into a textbook format, this second edition builds on the foundation of the 2013 lecture notes-style first edition, transforming it into an ideal resource for one-semester graduate or upper-level undergraduate courses. Retaining the original structure while significantly enhancing accessibility and depth, this edition features:

Readers with a college-level background in AI, computer science, or mathematical logic will find this book indispensable for understanding the principles and applications of NAL in AI development.

Contents:

• Introduction
• IL-1: Idealized Situation
• NAL-1: Basic Syntax and Semantics
• NAL-1: Basic Inference Rules
• NARS: Basics of Memory and Control
• NAL-2: Derived Copulas
• NAL-3: Set-theoretic Compound Terms
• NAL-4: Relational Terms
• NAL-5: Statements as Terms
• NAL-6: Variable Terms
• NAL-7: Events as Statements
• NAL-8: Operations and Goals as Events
• NARS+: Sensorimotor Capability
• NAL-9: Mental Operations and Meta-Goals
• Conclusions and Implications
• Appendix A: Narsese Grammar
• Appendix B: NAL Inference Rules
• Appendix C: NAL Truth-Value Functions
• Appendix D: Mental Operations
• Appendix E: Proofs of Theorems
• Appendix F: Solutions of Selected Exercises
• Appendix G: NARS Implementations

Readership: Readers with a college-level background in AI, computer science, or mathematical logic.