Showdown bot

by pmariglia

GitHub Readme.md

Showdown umbreon

Showdown is a Pokémon battle-bot that can play battles on Pokemon Showdown.

The bot can play single battles in generations 4 through 7 however some of the evaluation logic is assuming gen7 mechanics.

Python version

Developed and tested using Python 3.6.3.

Getting Started

Configuration

Environment variables are used for configuration which are by default read from a file named .env

The configurations available are:

SAVE_REPLAY: (bool, default False) Specifies whether or not to save replays of the battles
LOG_TO_FILE: (bool, default False) Specifies whether or not to write logs to files in {PWD}/logs/
LOG_LEVEL: (string, default "DEBUG") The Python logging level 
WEBSOCKET_URI: (string, default is the official PokemonShowdown websocket address: "sim.smogon.com:8000") The address to use to connect to the Pokemon Showdown websocket 
PS_USERNAME: (string, required) Pokemon Showdown username
PS_PASSWORD: (string) Pokemon Showdown password
DECISION_METHOD: (string, default "safest") The decision making method. Options are "safest" and "nash". More on this in the Decision Logic section
USE_RELATIVE_WEIGHTS: (bool, default False) Specifies whether or not to analyze each state and determine how valuable each pokemon is 
BOT_MODE: (string, required) The mode the the bot will operate in. Options are "CHALLENGE_USER", "SEARCH_LADDER", or "ACCEPT_CHALLENGE"
USER_TO_CHALLENGE: (string, required if BOT_MODE is "CHALLENGE_USER") The user to challenge
POKEMON_MODE: (string, required) The type of game this bot will play games in
TEAM_NAME: (string, required if POKEMON_MODE is one where a team is required) The name of the JSON file that contains the team you want to use. More on this below in the Specifying Teams section.
RUN_COUNT: (integer, required) The amount of games this bot will play before quitting

Here is a minimal .env file. This configuration will log-in and search for a gen7randombattle:

WEBSOCKET_URI=sim.smogon.com:8000
PS_USERNAME=MyCoolUsername
PS_PASSWORD=MySuperSecretPassword
BOT_MODE=SEARCH_LADDER
POKEMON_MODE=gen7randombattle
RUN_COUNT=1

Running without Docker

Clone

Clone the repository with git clone https://github.com/pmariglia/showdown.git

Install Requirements

Install the requirements with pip install -r requirements.txt.

Be sure to use a virtual environment to isolate your packages.

Run

Running with python run.py will start the bot with configurations specified by environment variables read from a file named .env

Running with Docker

Clone the repository

git clone https://github.com/pmariglia/showdown.git

Build the Docker image

docker build . -t showdown

Run with an environment variable file

docker run --env-file .env showdown

Running on Heroku

Deploy

After deploying, go to the Resources tab and turn on the worker.

Decision Logic

The bot searches through the game-tree for two turns and can make a decision in the two different ways explained below.

For decisions with random outcomes a weighted average is taken for all possible end states. For example: If using draco meteor versus some arbitrary other move results in a score of 1000 if it hits (90%) and a score of 900 if it misses (10%), the overall score for using draco meteor is (0.9 * 1000) + (0.1 * 900) = 990.

Most aspects of Pokémon are accounted for, such as:

  1. Damage Rolls

  2. Spreads

  3. Move-Sets

  4. Abilities

  5. Items

  6. Hazards

  7. Weather

Relative Pokemon Weights

A natural strategy in Pokémon is to preserve win-conditions. The bot attempts to do this by assigning each Pokémon a multiplier based on how valuable they are in defeating the opponent's team. Experimentation with this has proven to produce better results on the PokemonShowdown ladder.

Decision Methods

Safest

use DECISION_LOGIC=safest (default unless otherwise specified)

Safest means that the bot will make a move that minimizes the possible loss for a turn. This is equivalent to the Maximin strategy

This decision type is deterministic - the bot will always make the same move given the same situation again.

Nash-Equilibrium (experimental)

use DECISION_LOGIC=nash

Using the information it has, plus some assumptions about the opponent, the bot will calculate the Nash-Equilibrium with the highest payoff and select a move from that distribution.

The Nash Equilibrium is calculated using command-line tools provided by the Gambit project. This decision method should only be used when running with Docker and will fail otherwise.

This decision method is not deterministic. The bot may make a different move if presented with the same situation again.

Performance

The bot will perform best when using the "safest" decision making method and when taking the time to give each Pokémon a multiplier before deciding a move.

These are the current results in three different formats for roughly 75 games played on a fresh account:

RelativeWeightsRankings

Specifying Teams

The user can specify teams in JSON format to be used for non-random battles. Examples can be found in teams/team_jsons/.

The name of the .json file must used as TEAM_NAME in the configuration file.

For example, this repository contains two sample teams: ou_sample.json, and pu_sample.json.

Those teams can be used with the configuration TEAM_NAME=ou_sample or TEAM_NAME=pu_sample respectively.