Advances in Neuro Symbolic Reasoning and Learning

Thank you for to all who attended our 2023 tutorial at AAAI!

Part 1: Introduction and overview of neuro symbolic frameworks for reasoning and learning (Shakarian)

Part 2: Neuro symbolic based approaches for deduction (Simari)

Part 3: Combining perceptual neural networks with logic and applications (Baral)

Part 4: Neuro-Symbolic Learning and Reasoning: Challenges and Opportunities (Velasquez)

Unfortunately, video from the event is not available, but you can see related video content at: https://www.youtube.com/@neurosymbolic

Companion book: https://neurosymbolic.asu.edu/advances-in-neuro-symbolic-reasoning-and-learning/

Tutorial description

Over the past five years, the community has made significant advances in neuro symbolic reasoning (NSR).  These NSR frameworks are now capable of embedding prior knowledge in deep learning architectures, guiding the learning process with logical constraints, providing symbolic explainability, and using gradient-based approaches to learn logical statements.  At this time, several approaches are seeing usage in various application areas.  This tutorial is designed for researchers looking to understand the current landscape of NSR research as well as those looking to apply NSR research in areas such as natural language processing and verification.  The pace of progress in NSR is expected to continue as firms such as IBM, Samsung, and Lockheed-Martin are now heavily investing in research in this area in addition to the recently announced government-funded efforts such as DARPA’s ASNR program indicate that this area will grow. A secondary goal of this tutorial is to help build a larger community around this topic as more basic researchers and applied scientists turn to NSR to build upon the successes of deep learning.  Attendees of the tutorial should be familiar with concepts in deep learning and logical reasoning, have mathematical maturity, as well as a basic understanding of fuzzy/real-valued logic.