a simple proof system I made to learn math without any mistakes

Overview

math_up

a simple proof system I made to learn math without any mistakes




0. Short Introduction


test yourself, enjoy your math!

math_up is an NBG-based, very simple but programmable proof verifier written in Python.
Some notable features are:

  • super-simplicity, short learning time
  • programmability
  • fully written in Python (including all the proofs!)
  • trade-off between runtime efficiency & reductionism
  • non-generic implementation (supports only 1st-order logic, NBG set theory)
  • supports on Fitch-style proofs, "let" variables and many other intuitive APIs
  • rule-based, without any AI-like things

The following sections assumes you already know basic concepts on logic and set theory.

Author : Hyunwoo Yang
  • Department of Mathematical Sciences, Seoul National University (2013 ~ 2019)
  • Modem R&D Group, Samsung Networks (2019 ~ )

1. Sentence Generation


1-1. Variables

You may use alphabets from a to z, and also from A to Z.
Just calling clear() assures all the variables are new:

clear() # clear all alphabets

1-2. Atomic Properties

YourPropertyName = make_property("its_formal_name") # required at the first time
YourPropertyName(a, b) # usage

If the property is a binary relation, you can use operator overloading.
For example:

a 

1-3. Logical Connections

~ P         # not P
P & Q       # P and Q
P | Q       # P or Q
P >> Q      # P imply Q
P == Q      # P iff Q
true        # true
false       # false

1-4. Quantifiers

All(x, y, P(x, y)) # for all x and y, P(x, y)
Exist(x, y, z, P(x, y, z)) # there exists x, y and z such that P(x, y, z)
UniquelyExist(a, P(a, t)) # a is the only one such that P(a, t) 

1-5. Functions

YourFunctionName = make_function("its_formal_name") # required at the first time
YourFunctionName(x, y, z) # usage

If the function is a binary operator, you can use operator overloading.
For example:

x 

2. Numbering or Naming Statements

(your_sentence) @ 193
(your_sentence) @ "my_theorem"

Each number allows reuses, but the string names must be unique.
Hence, please number the sentences during the proof, but name the theorem at the last.

3. Inferences

(your_sentence) @ (save_as, INFERENCE_TO_USE, *arguments, *reasons)

save_as is a number or string you'd like to save your_sentence as.
INFERENCE_TO_USE depends on the inference you want to use to deduce your_sentence.
Some arguments are required or not, depending on the INFERENCE_TO_USE
reasons are the numbers or strings corresponding to the sentences already proved, which are now being used to deduce your_sentence.

3-1. DEDUCE

with (your_assumption) @ 27 :
    # your proof ...
    (your_conclusion) @ (39, SOME_INFERENCE, argument0, argument1, reason0, reason1)
(your_assumption >> your_conclusion) @ (40, DEDUCE)

math_up supports Fitch-style proofs.
That means, you may make an assumption P, prove Q and then deduce (P implies Q).
The inference to use is DEDUCE. DEDUCE doesn't require any arguments or reasons, but it must follow right after the end of the previous with block.

3-2. TAUTOLOGY

(A >> B) @ (152, INFERENCE0, argument0, reason0, reason1)
A @ (153, INFERENCE1, argument1, argument2, reason2)
B @ (154, TAUTOLOGY, 152, 153)

When is statement is a logical conclusion of previously proved sentences, and it can be checked by simply drawing the truth table, use TAUTOLOGY.
It doesn't require any arguments.
Put the sentences needed to draw the truth table as reasons.

3-2. DEFINE_PROPERTY

(NewProperty(x, y) == definition) @ ("save_as", DEFINE_PROPERTY, "formal_name_of_the_property")

You can freely define new properties with DEFINE_PROPERTY.
It does not requires any reasoning, but requires the formal name of the new property as the only argument.

3-3. DEFINE_FUNCTION

All(x, y, some_condition(x, y) >> UniquelyExist(z, P(x, y, z))) @ (70, INFERENCE0)
All(x, y, some_condition(x, y) >> P(x, y, NewFunction(z))) @ ("save_as", DEFINE_FUNCTION, 70)

Defining new function requires a sentence with a uniquely-exist quantifier.
Using DEFINE_FUNCTION, you can convert (for all x and y, if P(x, y) there is only one z such that Q(x, y, z)) into (for all x and y, if P(x, y) then Q(x, y, f(x, y)))
It requires no arguments, but one uniquely-exist setence as the only reason.


3-4. DUAL

(~All(x, P(x)) == Exist(x, ~P(x))) @ (32, DUAL)
((~Exist(y, Q(z, y))) == All(y, ~Q(z, y))) @ (33, DUAL)

not all == exist not, while not exist == all not.
To use these equivalences, use DUAL.
It requires no arguments or reasons.

3-5. FOUND

P(f(c)) @ (5, INFERENCE0, argument0)
Exist(x, P(x)) @ (6, FOUND, f(c), 5)

If you found a term satisfying the desired property, you can deduce the existence by FOUND.
It requires the term you actually found as an argument, and a sentence showing the desired property as the only reason.

3-6. LET

Exist(x, P(x)) @ (6, INFERENCE0, argument0, 5)
P(c) @ (7, LET, c, 6)

This one is the inverse of FOUND- i.e. it gives a real example from the existence.
It requires a fresh variable(i.e. never been used after the last clean()) to use as an existential bound variable as an argument.
Also, of course, an existential statement is required as the only reason.

3-7. PUT

All(x, P(x, z)) @ (13, INFERENCE0, 7, 9)
P(f(u), z) @ (14, PUT, f(u), 13)

PUT is used to deduce a specific example from the universally quantifiered sentence.
The term you want to put is an argument, and of course, the universally quantifiered sentence is the only reason.

3-8. REPLACE

P(x, a, a)
(a == f(c)) @ (8, INFERENCE0, argument0, 7)
P(x, a, f(c)) @ (9, REPLACE, 8)

When the two terms s and t are shown to be equal to each other, and the sentence Q is obtained from a previously proved P by interchainging s and t several times, REPLACE deduces Q from the two reasoning, i.e. s == t and P.
No arguments are needed.

3-9. AXIOM

any_sentence @ ("save_as", AXIOM)

AXIOM requires no inputs, but simply makes a sentence to be proved.

3-10. BY_UNIQUE

UniquelyExist(x, P(x)) @ (0, INFERENCE0)
P(a) @ (1, INFERENCE1, argument0)
P(f(b)) @ (2, INFERENCE2, argument1)
(a == f(b)) @ (3, BY_UNIQUE, 0, 1, 2)

BY_UNIQUE requires no arguments, but requires three reasons.
The first one is about unique existence, and the last two are specifications.
You can conclude two terms used for specifications respectively are equal to each other.
3-10. CLAIM_UNIQUE

Exist(x, P(x)) @ (6, INFERENCE0, argument0, 5)
P(c) @ (7, LET, c, 6)
P(d) @ (8, LET, d, 6)
# your proof ...
(c == d) @ (13, INFERENCE0, 12)
UniquelyExist(x, P(x)) @ (14, CLAIM_UNIQUE, 13)

CLAIM_UNIQUE upgrades an existence statement to a unique-existence statement.
Before you use it, you have to apply LET two times, and show the result variables are the same.
No arguments are required, but the equality is consumed as the only reason.

3-11. DEFINE_CLASS

UniquelyExist(C, All(x, (x in C) == UniquelyExist(a, UniquelyExist(b, (x == Tuple(a,b)) and Set(a) & Set(b) & P(a, b))))) @ (17, DEFINE_CLASS, C, x, [a, b], P(a, b))

This implements the class existence theorem of the NBG set theory.
No reasoning is required, but there are four arguments:
C : a fresh variable, to be a newly defined class
x : a fresh variable, to indicate the elements of C
[a, b, ...] : list of the components of x
P(a, b) : a condition satisfied by the components


4. Remarks


4-1. Trade-Off : Runtime Efficiency vs. Reductionism

The class existence theorem is actually not an axiom, but is PROVABLE, due to Goedel
However, proving it requires recursively break down all the higher-level definitions to the primitive ones
I'm afraid our computers would not have enough resourse to do such tedious computation...
Similarly, meta-theorems such as deduction theorem, RULE-C, function definition are NOT reduced by this program.


4-2. Trade-Off : Readability vs. Completeness

Actually, we need one more axiom: All(x, P and Q(x)) >> (P and All(x, Q(x)))
But I'll not implement this here... it may not, and should not be needed for readable proofs.
For the similar reasons, the program doesn't allow weird sentences like All(x, All(x, P(x))) or All(x, P(y)).
Strictly speaking, math_up is an incomplete system to restrict the proofs more readable.


4-3. Acknowledgement

Thanks to everyone taught me math & CS.
Mendelson's excellent book, Introduction to Mathematical Logic was extremely helpful.
Jech's Set Theory was hard to read but great.

Owner
양현우
양현우
Stack-overflow-import - Import arbitrary code from Stack Overflow as Python modules.

StackOverflow Importer Do you ever feel like all you’re doing is copy/pasting from Stack Overflow? Let’s take it one step further. from stackoverflow

Filip Haglund 3.7k Jan 08, 2023
A synchronous, single-threaded interface for starting processes on Linux

A synchronous, single-threaded interface for starting processes on Linux

Spencer Baugh 27 Jan 28, 2022
Traffic flow test platform, especially for reinforcement learning

Traffic Flow Test Platform Traffic flow test platform, especially for reinforcement learning, named TFTP. A traffic signal control framework that can

4 Nov 07, 2022
Simplified web browser made in python for a college project

Python browser Simplified web browser made in python for a college project. Web browser has bookmarks, history, multiple tabs, toolbar. It was made on

AmirHossein Mohammadi 9 Jul 25, 2022
Python script which synchronizes the replica-directoty with the original-one.

directories_synchronizer Python script which synchronizes the replica-directoty with the original-one. Automatically detects all changes when script i

0 Feb 13, 2022
Airplane reservation system python 2

airplane-reservation-system-python-2 Announcement 🔊 : 🔴 IMPORTANT 🔴 : Few new things have been added into the code [16/05/2021] different names is

voyager2005 1 Dec 06, 2021
Online learning platform

🛠 Status: In Development Teached is currently in development. So we encourage you to use it and give us your feedback, but there are things that have

Mohamed Nesredin 2 Feb 07, 2021
Software that extracts spreadsheets from various .pdf files to .csv

Extração de planilhas de diversos arquivos .pdf para .csv O código inteiro foi desenvolvido em Python. Foi utilizado o pacote "tabula" e a biblioteca

Marcos Silva 2 Jan 09, 2022
An example of python package

An example of python package Why use packages? It is a good practice to not code the same function twice, and to reuse common code from one python scr

10 Oct 18, 2022
sawa (ꦱꦮ) is an open source programming language, an interpreter to be precise, where you can write python code using javanese character.

ꦱꦮ sawa (ꦱꦮ) is an open source programming language, an interpreter to be precise, where you can write python code using javanese character. sawa iku

Rony Lantip 307 Jan 07, 2023
From "fixed RAnDom CRashes" to "[FIX] Fixed random crashes."

Clean Commit From fixed RAnDom CRashes to [FIX] Fixed random crashes. Clean commit helps you by auto-formating your commits to make your repos better

Mathias 3 Dec 26, 2021
This script can be used to get unlimited Gb for WARP.

Warp-Unlimited-GB This script can be used to get unlimited Gb for WARP. How to use Change the value of the 'referrer' to warp id of yours You can down

Anix Sam Saji 1 Feb 14, 2022
Simply create JIRA releases based on your github releases

Simply create JIRA releases based on your github releases

8 Jun 17, 2022
Python Function to manage users via SCIM

Python Function to manage users via SCIM This script helps you to manage your v2 users. You can add and delete users or groups, add users to groups an

4 Oct 11, 2022
Скрипт позволяет выгрузить участников чатов/каналов(по чату для комментариев) и сообщения в различные форматы файлов.

TG-Parser Парсер участников и сообщений из ТГ-Чатов и чатов для комментариев в ТГ-Каналах Возможности Выгрузка участников групп/каналов(по чату для ко

50 Jan 06, 2023
A Classroom Engagement Platform

Project Introduction This is project introduction Setup Setting up Postgres This is the most tricky part when setting up the application. You will nee

Santosh Kumar Patro 1 Nov 18, 2021
Simple dependency injection framework for Python

A simple, strictly typed dependency injection library.

BentoML 14 Jun 29, 2022
Cute study buddy that helps you study with the Pomodoro technique!

study-buddy Cute study buddy that helps you study with the Pomodoro (or Animedoro) technique! Kirby The Kirby folder has a Kirby, pink-themed Pomodoro

Ethan Emmanuel 1 Jan 19, 2022
Structured Exceptions for Python

XC: Structured exceptions for Python XC encourages a structured, disciplined approach to use of exceptions: it reduces the overhead of declaring excep

Bob Gautier 2 May 28, 2021
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python

Scalene: a high-performance CPU, GPU and memory profiler for Python by Emery Berger, Sam Stern, and Juan Altmayer Pizzorno. Scalene community Slack Ab

PLASMA @ UMass 7k Dec 30, 2022