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Monopoly Malfeasance (Working Title), Game Board State (Physical pieces,…
Monopoly Malfeasance (Working Title)
Stage (1) Game Definition (Following a ruleset, controlling the state of the game, determining turn order etc.)
Game Score
Game initialization methods
Shuffling and Dealing Cards
Determine Turn Order
Stage (2) Player Decisions (What options the player has available to it at all stages of the game. Should be able to complete basic strategies, or follow strategies from stage 3)
Available Actions
Basic Behaviors (i.e. simple implementations of strategies)
Create a representation of the current hand as a input layer
Stage (3) Neural Network (Methods to learn from game state and player options to learn winning strategies)
Implement a basic neural network
Implement a basic monte carlo learning algorithm that uses value function approximation
Create more sophisticated learning algorithms such as TD(\lambda)
Stage (4) Statistics and content gathering (tools to try to learn what "strategy" the model is implementing)
Game Board State (Physical pieces, info about board tiles)
Active Decks
Containers of played cards
Players state on the board
Video Preparation Workflow
Audio/ scripting
Writing script
Library of sound effects
music for background
Record snippet clips
Visual
Screen recording plots
Screen recording looking at code
Fun animations or visual explanations
Content
Structured outline
Write code
Easily accessible version control for mistakes
Any silly jokes to lighten up the mood
Edit it all together
Game State (initial, active, complete)
End conditions
Number of Players (int)
Player turn (int or None)