Introduction to Formal Logic (and AI) Spring 2025 Edition of IFLAI1 (“eye” • “fly” • “one”) Selmer Bringsjord
Table of Contents
with Naveen Sundar G.
∧ KB Foushée ∧ \(\ldots\)
Figure 2: Larry
Figure 3: Lucy
[All artwork (all of which is copyrighted) for the LAMA® paradigm by KB Foushée.]
Terminology & General Orientation
This course is an advanced, accelerated introduction to deductive formal logic, with some substantive coverage of inductive formal logic, in which formalisms for dealing with uncertainty (e.g., probability theory, and also the likelihood calculus) are included, and to heterogeneous formal logic (which allows reasoning over not only textual/linguistic content, but visual content as well). The course conforms to the LAMA® paradigm in general, and is specifically based on Hyperlogic:®, which among other things (all of which are explained and covered) is based on the view that proofs and arguments are best cast as hypergraphs. Since the present course emphasizes deduction, the course is specifically based on hypergraphical natural deduction. This is the only robust treatment of formal logic based on this form of deduction, which has many unique advantages.
The course makes crucial use of patented AI for learning, and also provides an introduction to AI itself, at least AI of the logicist variety. In particular, and for example, students are exposed to pure general logic programming (abbreviated PGLP), a new logic-programming paradigm particularly well-suited to pursuing logicist AI; students are also introduced to the new PGLP programming language and environment *Hyperlog*®. In addition, students are educated about the part of AI known as automated reasoning, which in general consists in AI itself reasoning in both deductive and inductive fashion. (Today’s irrational euphoria about AI has resulted in some obscure conceptions of “reasoning” that are that depressingly illogical; see e.g. the one given here.)
The last part of the class includes distinctive coverage of some of the great theorems proved by humanity’s greatest logician: Kurt Gödel.
- Terminology
Note that sometimes ‘symbolic’ is used in place of ‘formal.’ This is bad practice, since formal logic includes heterogeneous logics in which not only symbolic, but also pictorial information, figures. Deductive formal logic is a superset of mathematical logic; the latter is the part of deductive formal logic devoted to the mathematical analysis of mathematics itself (which is why some also use the term ‘meta-mathematics’ to denote mathematical logic). Part of the present course is devoted to mathematical logic. The specific phrase used to describe what the student is principally introduced to in this class is: beginning deductive logic, advanced (BDLA); hence the title of our textbook (see below).
- What Next?
After this class, the student can proceed to the intermediate level in formal deductive and inductive logic, and — with a deeper understanding and better prepared to flourish — to various areas within the formal sciences, which are invariably based on formal logic, at least to a high degree. The formal sciences include e.g. theoretical computer science (e.g., computability theory, complexity theory, rigorous coverage of programming and programming languages), mathematics in all its traditional branches (analysis, geometry, topology, etc), decision theory, (economic) game theory, set theory, probability theory, etc. The class also serves as a stepping stone to further study of AI, of formal/theoretical computer science, and of in-depth logic programming.
- What is Formal Logic?
In general, formal logic is the science and engineering of reasoning,1 but even this supremely general description fails to convey the flexibility and enormity of the field. For example, the vast majority of classical mathematics can be deductively derived from a small set of formulae (including, e.g., ZFC set theory, which you’ll be hearing more about, and exploring) expressed in the particular formal logics known as ‘first-order logic’ (FOL = \(\mathscr{L}_1\)) and ‘second-order logic’ (= SOL = \(\mathscr{L}_2\)); you’ll also be hearing more about both of these logics as well. In addition, computer science emerged from and is in large part based upon logic (for peerlessly cogent yet non-technical coverage of this emergence, see C Glymour’s Thinking Things Through). Logic is indeed the foundation for all at once rational-and-rigorous intellectual pursuits. (If you can find a counter-example, i.e. such a pursuit that doesn’t directly and crucially partake of logic, S Bringsjord would be very interested to see it.)
- Context: A Research University
You have wisely decided to attend a technical research university, with a faculty-led mission to create new knowledge and technology in collaboration with students. RPI is the oldest such place in the English-speaking world; it may know a thing or two about this mission. The mission drives those who teach you in this class. The last thing we want to do is simply convey to you how others present and teach introductory formal logic. As should be obvious by now, Bringsjord thinks he has with others in Motalen invented a better way to define, specify, and present formal logic, and to use computational formal logic for AI, and he is toiling to explain this invention, to explain it to others, and to disseminate the invention in question. The better way in question is denoted (i) by the phrase ‘Logic: A Modern Approach®,’ or simply by the abbreviation ‘LAMA®,’ pronounced so as to rhyme with ‘llama;’ and (ii) by the word ‘Hyperlog.’
- A Disclaimer!
Please note that guest lecturers other than NS Govindarajulu and A Bringsjord should not be assumed to have fully affirmed the LAMA® paradigm. This thus applies specifically to any and all TAs and graduate students. As to what these other thinkers hold in connection with LAMA®, that is an open question. You are free and indeed encouraged to inquire!
- Graduate Teaching Assistants; Further Help
The TA for this Spring 2025 edition of the course is PhD student James Oswald, an expert on computational logic and AI, and especially AGI (
oswalj@rpi.edu). Please note again the subsection A Disclaimer!. - Prerequisites
There are no formal prerequisites. However, as said above, this course covers formal logic, and though the course is an introduction, it has also been said above that it’s an advanced, accelerated one. This implies that — for want of a better phrase — students are expected to have a degree of logico-mathematical maturity, achieved for example through mastery of first-rate coverage of high-school mathematics. You have this maturity and mastery on the assumption that you understood the math you were supposed to learn in order to make it where you are. For example, to get to where you are now, you were supposed to have learned the technique of indirect proof (= proof by contradiction = reductio ad absurdum), from either or both of the courses Algebra 2 and Geometry. An example of the list of concepts and techniques you are assumed to be familiar with from high-school geometry can be found in the common-core-connected Geometry: Common Core by Bass et al., published by Pearson in 2012. An example of the list of concepts and techniques you are assumed to be familiar with from high-school Algebra 2 can be found in the common-core-connected Algebra 2: Common Core by Bellman et al., published by Pearson, 2012. It’s recommended that during the first two weeks of the class, students review their high-school coverage of formal logic. While this material will be covered from scratch in this class, it helps to have at least some command of it from high school, since our pace will be a rapid one. A much more robust treatment of prerequisites and a suitable background for this course is provided in the syllabus.
Texts/Readings
Students will purchase access to (and in the case of the e-textbook, obtain) the inseperably interconnected trio of
- HyperGrader®, a comprehensive, patented (Patent No. US 11,526,779 B2) and Pat. Pend. AI platform generating, assessing, tracking, and broadcasting (in anonymized form on leaderboards) problems, the tackling of which largely takes place in
- the patented HyperSlate® AI system for (among other things) proof and logic-progam construction in collaboration with AI technology; and
- the (copyrighted) e-textbook Logic: A Modern Approach; Beginning Deductive Logic via HyperSlate®, Advanced (LAMA-BDLAHS).
Each member of this trio will be available online after purchase of the relevant code-carrying envelope from or in the RPI Follett Bookstore. Full logistics of this purchase, and the content of the envelope and how to proceed from this content, will be explained in the first class (and subsequently, in greater detail, with walk-throughs given live). Updates to LAMA-BDLAHS, and additional exercises, will be provided by listing on relevant LAMA® web pages upon signing in to HyperGrader® (and sometimes by email) through the course of the semester. You will need to manage many electronic files as this course proceeds, and e-housekeeping and e-orderliness are of paramount importance. You will specifically need to assemble a library of completed and partially completed proofs in the cloud so that you can use them as building blocks in harder proofs; in other words, building up your own “logical library” will be crucial. This will be your library in HyperSlate®.
Please note that both HyperGrader® and HyperSlate® are both patented, copyrighted, trademarked AI systems; copying and/or reverse engineering or distributing this software to others is strictly prohibited by law. You will need to AGREE online (after registration) to a License Agreement. This agreement will also cover the e-textbook, which is copyrighted as well, and cannot be copied or distributed in any way, even in part.
In addition, occasionally papers may be assigned as reading. Three, indeed, were assigned in the syllabus, on the first day of class.
As to AI, it’s strongly recommended that students read the online summary of AI provided by Bringsjord & Govindarajulu, available here.
Finally, slide decks used in class will contain crucial additional content above and beyond LAMA-BDLA, information posted on HyperGrader®, and on HyperSlate®; this additional content will be available on the web site as the course unfolds through time.
Syllabus
The version of the course now underway is the Spring 2025 edition, the syllabus for which is available here. This is a robust, detailed syllabus, and is required reading — and reading that will pay off, for sure.
HyperSlate®
This is the patented intelligent software system used for constructing proofs, arguments, and logic programs in collaboration with AI technology, and is available after registration and sign-in.
HyperGrader®
This is the patented overarching AI platform (via which HyperSlate® is accessed) for submitting, getting assessed, and earning points for proofs and arguments constructed in HyperSlate®, and is available after registration and by sign-in.
LAMA-BDLAHS Textbook
This is the e-textbook for the course, and is obtained after registration and sign-in, by downloading fromm HyperGrader®.
Class-Day Content
- January 6 2025: General Orientation to the LAMA® Paradigm, Logistics, Mechanics. (S Bringsjord)
The syllabus was projected and presented, and discussed, in detail. Please note that the syllabus, in particular, makes clear that students who wish to opt for learning under a different paradigm and a different collection of software systems than that of LAMA® and its patented and Pat. Pend. AI systems should take Intro to Logic in a Fall semester, since the “Stanford paradigm” is in use then.
- January 8 2025: The Immaterial Paradise; Motivating Paradoxes, Puzzles, and \mathcal{R}, Part I (a.k.a. “Why Study Logic?”; S Bringsjord)
The many answers to the “Why study formal logic?” question are enumerated, and explained. An avowal of Bringsjord’s immaterialist position on formal logic and human cognition is included. Students for whom all the problems presented are a breeze, can conceivably test out of the course, but one specific requirement in that regard is that such a student must’ve arrived from high school math and/or computer science with full command of explosion [viz. ∀ Φ, φ, ψ: if Φ ⊢ φ ∧ ¬ φ, then Φ ⊢ ψ], which is needed at a key juncture in this lecture.
Tutorials (expands as semester unfolds)
- Getting Registered with HyperGrader®/HyperSlate®
A vintage-but-still-helpful simple tutorial is available here, in which someone registers into the HyperGrader® platform, and then activates HyperSlate® to prove that switching the order of conjuncts is provable in the propositional calculus = \(\mathscr{L}_{PC}\). This proof wins a trophy and earns a leaderboard spot for the Exercise
switching_conjuncts_fine. - Switching Disjuncts is Fine (under 90 sec)
- Just click here.
- Getting Started with HyperSlate®: Propositional Calculus
In this tutorial, available here, S Bringsjord starts from scratch with a blank workspace and uses HyperSlate® and the PC provability oracle available therein to show that the atomic proposition \(h\) can be deduced from \(\{\neg \neg c, c \rightarrow a, \neg a \vee b, b \rightarrow d, \neg (d \vee e)\}\). The main purpose of this video is coverage of the intuitive interface and basic moves therein.
Live Logic
These problems are timed and released in HyperGrader® in the absence of any preceding announcement that they are coming. Please see the syllabus for more information.
Homeworks
Homework consists of solving all Required problems listed on HyperGrader®’s web pages. (Non-required problems are clearly marked as such, e.g. as Bonus Problems.) All solutions are created in their final form in HyperSlate®. HyperGrader® for interactive use via its underlying AI technology opens for its Spring 2025 stint at RPI student use on or about Jan 23 2025, and an orientation/introduction to the system is given in class that day. Note that homeworks cannot be done without access to, and sustained and continuous use of, HyperSlate®, access via the AI platform HyperGrader®.
Tests
There are three tests, each presented and taken online and outside of class via HyperGrader®. Please see the syllabus for their release dates.
Footnotes:
Warning: Increasingly, the term ‘reasoning’ is used by some who don’t really do anything related to reasoning, as traditionally understood, to nonetheless label what they do. Fortunately, it’s easy to verify that some reasoning is that which is covered by formal logic: If the reasoning is explicit; links declarative statements or formulae together via explicit, abstract reasoning schemata or rules of inference (giving rise to at least explicit arguments, and often proofs); is surveyable and inspectable, and ultimately machine-checkable; then the reasoning in question is what formal logic is the science and engineering of. (An immediate consequence of the characteristics just listed is that AIs based on artificial neural networks don’t reason, ever.) In order to characterize /in/formal logic, one can remove from the previous sentence the requirements that the links must conform to explicit reasoning schemas or rules of inference, and machine-checkability. It follows that so-called informal logic would revolve around arguments, but not proofs. An excellent overview of informal logic, which will be completely ignored in this class, is provided in “Informal Logic” in the Stanford Encyclopedia of Philosophy. In this article, it’s made clear that, yes, informal logic concentrates on the nature and uses of argument.