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https://github.com/alexandrecarlton/pokemon-chain-breeding-solver
A solver for determining the shortest set of breeding steps to breed an egg move onto a pokemon
https://github.com/alexandrecarlton/pokemon-chain-breeding-solver
breeding clingo pokemon
Last synced: 11 days ago
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A solver for determining the shortest set of breeding steps to breed an egg move onto a pokemon
- Host: GitHub
- URL: https://github.com/alexandrecarlton/pokemon-chain-breeding-solver
- Owner: AlexandreCarlton
- Created: 2024-12-10T12:13:07.000Z (12 days ago)
- Default Branch: master
- Last Pushed: 2024-12-10T12:14:23.000Z (12 days ago)
- Last Synced: 2024-12-10T13:24:19.203Z (12 days ago)
- Topics: breeding, clingo, pokemon
- Language: Python
- Homepage:
- Size: 3.91 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Pokemon Chain Breeding Solver
Determines a shortest set of breeding steps to produce a pokemon with a given
move.
## Motivation
Pokemon may learn [move](https://bulbapedia.bulbagarden.net/wiki/Move)s in a
variety of ways, including via [levelling up](https://bulbapedia.bulbagarden.net/wiki/Level)
or by [TM](https://bulbapedia.bulbagarden.net/wiki/TM)/[HM](https://bulbapedia.bulbagarden.net/wiki/HM).
In particular, a pokemon may learn a given move if the father (or mother,
post-Generation VI) knows the move. As an example, if a Male Skity knowing Wish
breeds with a female Eevee, the resulting offspring (an Eevee) will also know
Wish, despite Eevee not learning Wish via level-up or TM/HM. These moves are
termed [Egg move](https://bulbapedia.bulbagarden.net/wiki/Egg_Move)s.
However, in the above eample, Skitty _also_ can only learn Wish as an Egg Move.
We thus need to determine:
- a "starting" parent that learns the move not as an Egg move.
- the shortest sequence of breeding steps to produce the desired Pokemon with
the Egg move.
## Dependencies
- [clingo](https://github.com/potassco/clingo)
- [Python](https://www.python.org/)
- [Docker](https://www.docker.com/)
## Running
### Setup
We first need to produce a `dump.json` that can be re-used for solving. To
generate it, run the following script:
```sh
./dump.py
```
This only needs to be executed once.
### Solving
Run `solve.py`:
```sh
./solve.py -m wish -p eevee -v emerald
```
This will produce ouput like the following:
```
...
Solving...
Answer: 1
can_breed(skitty,eevee) can_breed(togetic,skitty)
Optimization: 2
OPTIMUM FOUND
...
```
This tells us that we found a the shortest set of breeding steps:
- `togetic` / `skitty`
- `skity` / `eevee`
This means we need to:
- obtain a male Togetic that has learned the move Wish (which it can do via level-up),
- breed it wih a female Skitty to obtain a male Skitty wih Wish.
- breed this male Skitty wih a female Eevee to obtain an Eevee wih Wish.
## How it works
### [`dump.py`](./dump.py)
[`dump.py`](./dump.py) will pull down an [optimized dump](https://github.com/AlexandreCarlton/pokeapi-dump)
of [PokeAPI](https://pokeapi.co/) and produce a `dump.json` containing, for all pokemon:
- egg moves across all version groups
- gender rates
- egg groups
This only needs to be run once; the `dump.json` can be re-used by the next
step.
### [`solve.py`](./solve.py)
[`solve.py`](./solve.py) is the workhorse of this project. It takes in:
- a target pokemon
- the desired egg move for the target pokemon
- a version group (e.g. Crystal, Ruby/Sapphire)
and produces a minimal set of 'facts' as can be interpreted by
[Clingo](https://github.com/potassco/clingo) (a logic solver). An example of
these facts is as follows:
```prolog
learns_via(eevee, egg).
learns_via(skitty, egg).
learns_via(togetic, level_up).
% ...
egg_group(eevee, ground).
egg_group(skitty, ground).
egg_group(skitty, fairy).
egg_group(togetic, fairy).
egg_group(togetic, flying).
% ...
gender_rate(eevee, 1).
gender_rate(skity, 6).
gender_rate(togetic, 1).
```
We generate as few facts as possible to optimise Clingo's solving; as such, we
only:
- generate `learns_via` facts for the desired move.
- generate `egg_group` facts for pokemon found in `learns_via`.
- generate `gender_rate` facts for pokemon found in `learns_via`.
We then combine this file with [`solver.pl`](./solver.pl) and run it through
Clingo. This `solver.pl` will try to find the minimal set of breeding steps
(should such a set exist) to produce a pokemon - the above example will
produce:
```
...
Solving...
Answer: 1
can_breed(skitty,eevee) can_breed(togetic,skitty)
Optimization: 2
OPTIMUM FOUND
...
```
## Further reading
- [Chain breeding](https://bulbapedia.bulbagarden.net/wiki/Chain_breeding)
- [Programming with CLINGO](https://www.cs.utexas.edu/~vl/teaching/378/pwc.pdf)
- [A User’s Guide to gringo, clasp, clingo, and iclingo](https://wp.doc.ic.ac.uk/arusso/wp-content/uploads/sites/47/2015/01/clingo_guide.pdf)