Lego Computer Science: Truth Tables

by Paul Curzon, Queen Mary University of London

Lego of a truth table for NOT P

Truth tables are a simple way of reason about logic that were popularised by the 20th century philosopher Ludwig Wittgenstein. They provide a very clear way to explain what logical operators like AND, OR and NOT mean (or in computational terms, what they do). They also give a simple way to do pure logical reasoning and so see if arguments follow logically. These logical operators crop up in logic circuits and in programs where decisions are being made so are vital to creating correct circuits and writing correct programs. Let’s see what a truth table is by making some from Lego.

Logic in Lego

First we need to represent the basic building blocks of logic in lego. We’ve seen in previous articles how to represent numbers, binary and even images in lego. We have seen that we do computation on symbols and we can use lego blocks as symbols. Logic can therefore be represented in lego symbols too.

We will look at a simple kind of logic called propositional logic (there isn’t actually just one kind of logic but lots of different kinds with different rules). Propositional logic is the simplest kind. It deals with propositions which are just statements that are either true or false (but we may not know which). For example, “Snoopy is a logician.” is a proposition. So are “The world is flat.”, “Water contains oxygen.” and “temperature > 0” as we might find in a program. For the purposes of logic itself, it doesn’t matter what the words actually mean or even what they are. We will therefore represent all propositions by square lego blocks of different colours.

Here we want the symbols to stand for logical things rather than numbers. There are lots of numerical values: things like 1, 5 and 77. There are only two logical values: TRUE and FALSE, often written just as T and F. We will use a blue lego block for the logical value TRUE, and a red block for the value FALSE. They are just symbols though so we could use any blocks and any colours, just as we could use other words for true and false as other languages do. We chose blue for true just because it rhymes so is easy to remember, and red more randomly because it is a common lego primary colour.

True and False lego. A square 2x2 blue block is True. A square 2x2 red block is false.
True and False lego. A square 2×2 blue block represents True. A square 2×2 red block is false.

What about representing the actual sentences stating purported facts like “Messi is the best footballer ever”, or in a program “n == 1”? Statements like this are called propositions. As far as reasoning logically goes the precise words or even language they are in do not matter. This is something Wittgenstein realised. When doing reasoning these basic propositions can be replaced by variables like P and Q and the logic won’t change. Rather than use letters we will just use different coloured lego blocks to stand for different propositions, emphasising that the words or even variable names do not matter. So we will use a yellow block for a variable P and a green block for a variable Q. Each of which could stand for absolutely any English proposition we like at any time (though if we want it to stand for a particular proposition then we should define which one clearly).

Yellow block for P and green block for Q
Propositional variables P and Q are represented by yellow and green blocks

Logical Symbols

What we are really interested in is not just true and false values but the logical operations on propositions. The core of these we use in everyday English: AND, OR and NOT, more technically known as conjunction, disjunction and negation in logic. There are several variations of the symbols used to represent these symbols just as there are for true and false. We will use the versions in lego as below.

Symbols for AND, OR and NOT in Lego
The logical operators AND, OR and NOT as lego symbols

These lego symbols will allow us to write out logical expressions about propositions: like “The cat is thirsty AND NOT the cat is hungry” which we might write in English as “The cat is thirsty and not hungry”. If we use a yellow block to mean “The cat is thirsty” and a green block to mean “The cat is hungry” then in lego logic we can write it as follows:

P AND (NOT Q) in Lego symbols
The cat is thirsty AND NOT the cat is hungry

Of course the yellow and green brick are variables so by changing the propositions they represent it can stand for other things. It can also represent: ” The moon is blue AND NOT The moon is made of cheese.” where the yellow brick represents “The moon is blue” and the green brick represents “The moon is made of cheese”.

Think up some statements that involve AND, OR and NOT and then build representations of then in lego logic like the above.

The meaning of logical connectives

The above gives us symbols for the logical connectives, but so far they have no meaning: it is just syntax. Perhaps you think you know what the words mean. We use words like and, or and not in language rather imprecisely at times based on dictionary-style definitions. They essentially mean the same in English as in logic, but we need to define what they mean precisely. We do not want two different people to have two slightly different understandings of what they mean. This is where truth tables come in. A truth table tells us exactly, and without doubt, what the symbols for the operators mean. The give what is called by computer scientists a formal semantics to the logical connectives.

Let’s look at NOT first. A truth table is just a table that includes as rows all the combinations of true and false values of the variables in a logical expression together with an answer for those values. For example a truth table for the operator NOT, so telling us in all situations what (NOT a) means, is:

A truth table for the NOT operator. Reading along the rows,

We can build this truth table in lego using our lego representation:

Lego of a truth table for NOT P

NOT only applies to one proposition, the one it negates, (it is a unary logical connective). That means we only need two rows in the table to cover the different possible values those propositions could stand for. AND (and OR) combine to two propositions (it is a binary logical connective). To cover all the possible combinations of the values of those propositions we need a table with four rows as there are four possibilities.

A truth table for the logical AND operator.

We can build this in Lego as:

Lego of a truth table for P AND Q

Reading along the rows this says that if both P and Q are blue (true) then the answer for P AND Q is true. Otherwise the answer is false (red). T

The following is the lego truth table for the logical OR operator

Lego of a truth table for P AND Q

The columns for the two variables yellow/green (P/Q) are the same, setting out all the possibilities. Now the answer is true (blue) if either operand is true (blue) and false (red) when both are false (red).

We have now created lego truth tables that give the meaning of each of these three logical connectives. They aren’t the only logical operators – in fact there are 8 possible binary ones. Have a go at building lego truth tables for other binary logical connectives such as exclusive-or which is true if exactly one of the operands is true, and equivalence which is true if both operands are the same truth value.

Truth tables give precise meanings to logical operators and so to logic. That is useful, but even more usefully, they give a way to reason logically in a clear, price way. By following a simple algorithm to build new truth tables from existing ones, we can prove general facts, that are ultimately about propositions, in lego… as we will see next.

Lego Computer Science

Image shows a Lego minifigure character wearing an overall and hard hat looking at a circuit board, representing Lego Computing
Image by Michael Schwarzenberger from Pixabay

Part of a series featuring featuring pixel puzzles,
compression algorithms, number representation,
gray code, binary and computation.

Lego Computer Science

Part 1: Lego Computer Science: pixel picture

Part 2: Lego Computer Science: compression algorithms

Part 3: Lego Computer Science: representing numbers

Part 4: Lego Computer Science: representing numbers using position

Part 5: Lego Computer Science: Gray code

Part 6: Lego Computer Science: Binary

Part 7: Lego Computer Science: What is computation (simple cellular automata)?

Part 8: Lego Computer Science: Truth tables

More on …

EPSRC supports this blog through research grant EP/W033615/1, The Lego Computer Science post was originally funded by UKRI, through grant EP/K040251/2 held by Professor Ursula Martin, and forms part of a broader project on the development and impact of computing.

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