Lecture 5: Propositional Logic - Reasoning

This lecture is part of the course “Foundations of Artificial Intelligence” developed by Dr. Ryan Urbanowicz in 2020 at the University of Pennsylvania’s Perelman School of Medicine. This is the first of three courses covering topics in artificial intelligence for application within the context of informatics and biomedical research. The course is divided into modules that cover (1) introductory/background materials, (2) logic, (3) other knowledge representation, (4) essentials of expert systems, (5) search, (6) uncertainty, and (7) advanced/auxiliary topics. These topics offer a global foundation for branches of AI application and research, including concepts that will later support a deeper understanding of inductive reasoning and machine learning. In a practical sense, this course focuses on how biomedical data can be organized, represented, interpreted, searched, and applied in order to derive knowledge, make decisions, and ultimately make predictions while avoiding bias.

This course was assembled using content from a wide variety of textbooks, slides, and lectures by various authors and speakers on the relevant topics. Some lectures were prepared and given by guest lecturers and thus have not been posted. At the time of posting, this course is in its second year so any feedback is welcome regarding any mistakes or suggested improvements.

Weblinks:

Chapters:
0:00 Introduction
1:46 Logic: Model
2:55 Knowledge Base
3:52 Entailment
11:56 Arguments
16:26 Inference Rules
20:32 Deductive Reasoning From a Knowledge Base
33:33 Conclusion

Corrections:
18:36 The example "It is not hot or it is dry" should be "It is not sunny or it is dry"

[patmull]

Wow. I'm speechless. Of all of the materials about (formal) logic I've ever found, this Is the most intuitive, yet complete. Thanks a lot!

[tecimgc]

I think I'm missing something. @6:45 we see an example where entailment is not symmetric. ~P |= (P=>Q), but not the other way around, but @8:40 it looks like the 2nd property of entailment is symmetry, so if ~P => (P=>Q), I should be able to say (P=>Q) =>~P, which seems wrong...

[FlonoTV]

Great lecture. Just a small feedback: on headphones, you can only hear the sound on the left ear. Changing the stereo sound to mono sound when exporting the video would resolve that problem.

[shehz]

@18:38 there seems to be a problem in the example. it should either be it is not sunny or it is dry or the final conclusion should be therefore it is sunny or dry

[abo-alhosam]

I am wondering how this knowledge of Propositional Logic and so would impact how good I am when implementing an expert system in practice? It seems that there is something I am missing, would you please clarify this.