Partial Orderings as Partial Information

Imagine you're solving a Sudoku — a small one, 4×4, with digits 1–4. You start with a few givens. Everything else is unknown.

13
4
2
13

Your starting state of knowledge — call it a0 — is a list of facts:

a0 = 1 at (1,1) 3 at (1,3) 4 at (2,2) 2 at (3,3) 1 at (4,2) 3 at (4,4)

By applying the rules, we can deduce new facts. Row 4 needs 2 and 4. Column 3 already has a 2, so (4,3) must be 4:

13
4
2
143
a1 = 1 at (1,1) 3 at (1,3) 4 at (2,2) 2 at (3,3) 1 at (4,2) 3 at (4,4) 4 at (4,3)

Each deduction gives a new state — a1, a2, and so on — each containing everything the previous one did, plus more.

We can order these states by how much they know. Write a ⊑ b when every fact in b is also in a — that is, a knows at least as much as b. As we learn more, we descend:

Try it yourself:

1 3
4
2
1 3
a0 =
1 at (1,1) 3 at (1,3) 4 at (2,2) 2 at (3,3) 1 at (4,2) 3 at (4,4)

But not all states are comparable. One person might know one fact while another knows a different one — each knows something the other doesn't.

a: 1 at (1,1)
b: 3 at (2,4)

Neither a ⊑ b nor b ⊑ a.

This is a partial order: reflexive, antisymmetric, transitive — but not every pair of elements is comparable.

We can compare representations of facts according to how much information they contain. This yields a partial order.
Lattices →