22 lines
1.3 KiB
Markdown
22 lines
1.3 KiB
Markdown
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# Project vacuumDecay
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Project vacuumDecay is a framework for building AIs for games.
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Avaible architectures are
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- those used in Deep Blue (mini-max / expecti-max)
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- advanced expecti-max exploration based on utility heuristics
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- those used in AlphaGo Zero (knowledge distilation using neural-networks)
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A new AI is created by subclassing the State-class and defining the following functionality (mycelia.py provies a template):
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- initialization (generating the gameboard or similar)
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- getting avaible actions for the current situation (returns an Action-object, which can be subclassed to add additional functionality)
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- applying an action (the state itself should be immutable, a new state should be returned)
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- checking for a winning-condition (should return None if game has not yet ended)
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- (optional) a getter for a string-representation of the current state
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- (optional) a heuristic for the winning-condition (greatly improves capability)
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- (optional) a getter for a tensor that describes the current game state (required for knowledge distilation)
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- (optional) interface to allow a human to select an action
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### Current state of the project
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It currently does not work and implements none of the named functionality in a working fashion.
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Experiment for TicTacToe, Dikehiker and an encryption-breaker for rc4 are being worked on.
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