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# propositional axioms for WaterWorld

Summary: The domain axioms for WaterWorld in propositional logic.

We summarize the details of how we choose to model WaterWorld boards in propositional logic: exactly what propositions we make up, and the formal domain axioms which capture the game's rules.

The board is fixed at 6×4, named AA,…,ZZ (with I and O omitted).

## Propositions

There are a myriad of propositions for WaterWorld, which can be grouped:

• Whether or not a location contains a pirate: A-unsafeA-unsafe, B-unsafeB-unsafe, …, Z-unsafeZ-unsafe.
• Whether or not a location contains no pirate: A-safeA-safe, B-safeB-safe, …, Z-safeZ-safe.

### Aside:

Yes, using the intended interpretation, these are redundant with the previous ones. Some domain axioms below will formalize this.
• Propositions indicating the number of neighboring pirates, to a location: A-has-0A-has-0, A-has-1A-has-1, A-has-2A-has-2, B-has-0B-has-0, B-has-1B-has-1, B-has-2B-has-2, …, H-has-0H-has-0, H-has-1H-has-1, H-has-2H-has-2, H-has-3H-has-3, …, Z-has-0Z-has-0, Z-has-1Z-has-1. These are all true/false propositions; — there are no explicit numbers in the logic. A domain axiom below will assert that whenever (say) B-has-1B-has-1 is true, then B-has-0B-has-0 and B-has-2B-has-2 are both false.

### Aside:

There is no proposition A-has-3A-has-3 — since location AA has only two neighbors. Similarly, there is no proposition B-has-3B-has-3. We could have chosen to include those, but under the intended interpretation they'd always be false.

These propositions describe the state of the underlying board — the model — and not our particular view of it. Our particular view will be reflected in which formulas we'll accept as premises. So we'll accept A-has-2A-has-2 as a premise only when AA has been exposed and shows a 2.

## The domain axioms

Axioms asserting that the neighbor counts are correct:

• Count of 0:
• “A0”: A-has-0B-safeG-safe A-has-0 B-safe G-safe
• “H0”: H-has-0G-safeJ-safeP-safe H-has-0 G-safe J-safe P-safe
• “Z0”: Z-has-0Y-safe Z-has-0 Y-safe
• Count of 1:
• “A1”: A-has-1B-safeG-unsafeB-unsafeG-safe A-has-1 B-safe G-unsafe B-unsafe G-safe
• “H1”: H-has-1G-safeJ-safeP-unsafeG-safeJ-unsafeP-safeG-unsafeJ-safeP-safe H-has-1 G-safe J-safe P-unsafe G-safe J-unsafe P-safe G-unsafe J-safe P-safe
• “Z1”: Z-has-1Y-unsafe Z-has-1 Y-unsafe
• Count of 2:
• “A2”: A-has-2B-unsafeG-unsafe A-has-2 B-unsafe G-unsafe
• “H2”: H-has-2G-safeJ-unsafeP-unsafeG-unsafeJ-safeP-unsafeG-unsafeJ-unsafeP-safe H-has-2 G-safe J-unsafe P-unsafe G-unsafe J-safe P-unsafe G-unsafe J-unsafe P-safe
There aren't any such axioms for locations with only one neighbor.
• Count of 3:
• “H3”: H-has-3G-unsafeJ-unsafeP-unsafe H-has-3 G-unsafe J-unsafe P-unsafe
There aren't any such axioms for locations with only one or two neighbors.

Axioms asserting that the propositions for counting neighbors are consistent:

• A-has-0A-has-1A-has-0 A-has-1
• A-has-0¬A-has-1A-has-0 A-has-1
• A-has-1¬A-has-0A-has-1 A-has-0
• B-has-0B-has-1B-has-2B-has-0 B-has-1 B-has-2
• B-has-0¬B-has-1¬B-has-2B-has-0 B-has-1 B-has-2
• B-has-1¬B-has-0¬B-has-2B-has-1 B-has-0 B-has-2
• B-has-2¬B-has-0¬B-has-1B-has-2 B-has-0 B-has-1
• H-has-0H-has-1H-has-2H-has-3H-has-0 H-has-1 H-has-2 H-has-3
• H-has-0¬H-has-1¬H-has-2¬H-has-3H-has-0 H-has-1 H-has-2 H-has-3
• H-has-1¬H-has-0¬H-has-2¬H-has-3H-has-1 H-has-0 H-has-2 H-has-3
• H-has-2¬H-has-0¬H-has-1¬H-has-3H-has-2 H-has-0 H-has-1 H-has-3
• H-has-3¬H-has-0¬H-has-1¬H-has-2H-has-3 H-has-0 H-has-1 H-has-2

Axioms asserting that the safety propositions are consistent:

• A-safe¬A-unsafeA-safe A-unsafe,
• ¬A-safeA-unsafeA-safe A-unsafe,
• Z-safe¬Z-unsafeZ-safe Z-unsafe,
• ¬Z-safeZ-unsafeZ-safe Z-unsafe.

This set of axioms is not quite complete, as explored in an exercise.

As mentioned, it is redundant to have both A-safeA-safe and A-unsafeA-unsafe as propositions. Furthermore, having both allows us to express inconsistent states (ones that would contradict the safety axioms). If implementing this in a program, you might use both as variables, but have a safety-check function to make sure that a given board representation is consistent. Even better, you could implement WaterWorld so that these propositions wouldn't be variables, but instead be calls to a lookup (accessor) functions. These would examine the same internal state, to eliminate the chance of inconsistent data.

Using only true/false propositions; without recourse to numbers makes these domain axioms unwieldy. Later, we'll see how relations and quantifiers help us model the game of WaterWorld more concisely.

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