UNRELEASED GAME – AVAILABLE
This game is still in active development and available to the public for purchase in it's unfinished state, either in Early-Alpha or Beta (or any status in between).
Ai-Board is s a mobile app, which includes a board game, with an in-built Machine-Learning Engine and a proprietary visual coding-language, which can be resolved into python.
In the Board Game, each side has the same number pawns: rocks, papers, scissors. The goal is to attack as many of your components pawns, while protecting as many of yours as possible, following the simple overarching rule: Rock smashes scissors, Scissors cuts paper, Paper wraps rock.
Each pawn starts off being able to move 2 steps forward or sideways (and always one less step backwards), however the number of allowed steps increase, each time it successfully reaches the opponent's base, after returning home.
It includes a single-player and multi-player modes. A multi-team
extension is currently in development.
The online multi-player section of the game allows the player to participate in multiple concurrent matches, in a design that is both unique and intuitive.
The Ai-Pro section of the game allows the player to write code that drives an AiBot, which can also play the board game.
The player is then able to play against his/her creation, or pit his/her creation against other's, or against the in-built AiBots.
The AiBot code is written in a built-in proprietary visual coding language (called NodeCode), allows you to construct logic by connecting nodes.
NodeCode also allows the player to see a python representation of their code.
The player is able to debug their code as well.
The built-in machine learning language enables the user, using intuitive functions, to ...
- train their AiBot to play the board game.
- breed their AiBot using Genetic algorithm.
- fine tune their AiBot using Genetic algorithm.
A few methodologies have not yet been released, although they are very near to being ready. Neural networks, Neuroevolution of Augmenting Topologies.
Ai-Board was recently released in 2019 having being independently developed for 4 grueling, after an initial 1 year of design and preparation.