https://github.com/rdbrck/bountysnake2017

The Robosnake: Redbrick's bounty snake for the Battlesnake 2017 AI competition
https://github.com/rdbrck/bountysnake2017

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The Robosnake: Redbrick's bounty snake for the Battlesnake 2017 AI competition

• Host: GitHub
• URL: https://github.com/rdbrck/bountysnake2017
• Owner: rdbrck
• License: mit
• Created: 2017-02-17T01:45:32.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-03-08T23:31:17.000Z (over 7 years ago)
• Last Synced: 2024-04-08T02:26:27.234Z (7 months ago)
• Language: Lua
• Homepage:
• Size: 228 KB
• Stars: 0
• Watchers: 14
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
```

      ______  _____  ______   _____  _______ __   _ _______ _     _ _______

     |_____/ |     | |_____] |     | |______ | \  | |_____| |____/  |______

     |    \_ |_____| |_____] |_____| ______| |  \_| |     | |    \_ |______

                                                                           

```

## About

The Robosnake was [Redbrick](http://www.rdbrck.com)'s bounty snake entry for the 2017 [Battlesnake](http://www.battlesnake.io) AI programming competition. It is written using [Lua](https://www.lua.org/) and designed to be run under [OpenResty](http://openresty.org/).

Our win conditions to claim the bounty were the following:

* Game is played on a 17 x 17 board

* 10 food are present on the board, at any given time

* API timeout of 1 second

* One-versus-one, last snake slithering wins the bounty.

Under these conditions, we won forty-two games and lost three, for a total win record of 42/45 or 93%.

## Strategy

The Robosnake makes use of [alpha-beta pruning](https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning) in order to make predictions about the future state of the game. All possible moves by ourselves are evaluated, as well as all possible moves by the enemy. The Robosnake will always select for itself the move that results in the best possible state of the game board, and it will select for the enemy the move that results in the worst possible state of the game board (from the Robosnake's point of view, that is).

In order to evaluate a particular game board state, we look at the following metrics to produce a numeric score:

* How much health do I have?

* How much health does the enemy have?

* How many moves are available to me from my current position?

* How many moves are available to the enemy from its' current position?

* How many free squares can I see from my current position? (flood fill)

* How many free squares can the enemy see from its' current position? (another flood fill)

* How close am I to food right now?

In the event that we're playing in an arena containing more than one enemy snake, the closest snake to the Robosnake will be chosen as the "enemy" for the purposes of algorithmic computation.

In the event that we're playing in an empty arena, the Robosnake will choose *itself* as the "enemy". This will often lead to hilarity.

A blog post that talks about the strategy in depth is here: https://rdbrck.com/2017/03/building-bounty-snake-post-mortem/

## Configuration

Configuration is done in `/config/http.conf`. 

* `RULES_VERSION` - this can be set to `2016` or `2017`. 

* `MAX_RECURSION_DEPTH` - this affects how far the alpha-beta pruning algorithm will look ahead. Increasing this will make the Robosnake much smarter, but response times will be much longer.

* `SNAKE_ID` - when using `2016` rules, this needs to be set to the ID sent by the Battlesnake client.