Systems and methods for slot machine game development utilizing graphic-based artificial intelligence game design systems
Systems and methods for developing a game of chance. The game of chance being at least partially developed using specialized artificial intelligence (AI) game design systems or specialized artificial intelligence game design system modules or components which may include different types of machine learning or training techniques, including supervised, unsupervised, reinforced, deep learning and artificial neural networks and/or similar and may include analyzing past game performance utilizing full, partial or estimated prior game performance data for developing slot machine game math models, slot machine game mechanics and associated game programming, slot machine game art and graphics, slot machine animations, slot machine game sound effects, partial or full slot machine game development, slot machine computer code, slot machine game quality assurance diagnosis and editing, slot machine game analytics, slot machine compliance, slot machine help screens, and slot game predictive models, etc.
1 . A gaming method comprising:
at least partially developing executable instructions or computer readable files related to graphical elements for a game of chance for a gaming machine using a graphics-based artificial intelligence game design system based upon machine learning training including analyzing past game performance, from other previously deployed games of chance wherein game of chance development occurs prior to: (i) a first submission of the game of chance to an independent testing laboratory for approval or certification; or (ii) allowing play of the game of chance for real-money play in a regulated gaming environment following approval or certification by the independent testing laboratory, and input past game performance using tiered scales based on importance;
utilizing an artificial general intelligence foundational model and universal translator including at least an input mechanism, and media encoding and transcoding router to (i) change input data type to a different media format or consolidate the input data type to a specific file type and (ii) direct the changed or consolidated input data type to a specific neural network in a transformer process and select an output with a highest probability variable, wherein the artificial general intelligence foundational model and universal translator is configured to develop its own goal-seeking and reward behavior, gather and/or create training data in real-time, institute its own guardrails and optimization networks, and learn by feeding its output back into the input mechanism to develop the executable instructions or computer readable files related to graphical elements for a game of chance for a gaming machine; and
utilizing the at least partially developed executable instructions or computer readable files to present and allow play of the game of chance with the graphical elements for the gaming machine, the gaming machine including at least one of a monetary input device configured to receive a physical item associated with a monetary value and/or cashless wagering, a user interface, at least one processor for running the at least partially developed executable instructions or computer readable files related to the graphical elements for the game of chance, a game display and memory in communication with the at least one processor.
2 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes utilizing at least partially supervised machine learning training to at least partially develop graphical elements for the game of chance.
3 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes at least a graphics-based game design system module utilizing at least partially supervised machine learning training to at least partially develop executable instructions or computer readable files.
4 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes at least a past game performance analytics module utilizing at least partially supervised machine learning training.
5 . The gaming method of any of claim 1, 2, 3 or 4 wherein the at least part developing executable instructions or computer readable files related to graphical elements for the game of chance for a gaming machine includes developing a graphic of at least one of a game character, a reel set, game symbols, free symbols, a game background, a game logo, a game progressive box, a game credit bar, a secondary game character, or a game persistence graphic.
6 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes utilizing at least partially unsupervised machine learning training to at least partially develop graphical elements for the game of chance.
7 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes at least a graphics-based artificial intelligence game design system module utilizing at least partially unsupervised machine learning training to at least partially develop executable instructions or computer readable files.
8 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes at least a past game performance analytics module utilizing at least partially unsupervised machine learning training.
9 . The gaming method of any of claim 1, 6, 7 or 8 wherein the at least partially developing executable instructions or computer readable files related to graphical elements for the game of chance for a gaming machine utilizes at least partially unsupervised machine learning training and includes developing a graphic of at least one of a game character, a reel set, game symbols, free symbols, a game background, a game logo, a game progressive box, a game credit bar, a secondary game character, or a game persistence graphic.
10 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes utilizing at least partially reinforced machine learning training to at least partially develop graphical elements for the game of chance.
11 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes at least a graphics-based artificial intelligence game design system module utilizing at least partially reinforced machine learning training to at least partially develop executable instructions or computer readable files.
12 . The gaming method of claim 1 wherein the graphics-based artificial intelligence game design system includes at least a past game performance analytics module utilizing at least partially reinforced machine learning training.
13 . The gaming method of any of claim 1, 10, 11 or 12 wherein the at least partially developing executable instructions or computer readable files related to graphical elements for a game of chance for the gaming machine utilizes at least partially reinforced machine learning training and includes developing a graphic of at least one of a game character, a reel set, game symbols, free symbols, a game background, a game logo, a game progressive box, a game credit bar, a secondary game character, or a game persistence graphic.
14 . A gaming system comprising:
at least one processor running at least a portion of developed executable instructions or computer readable files related to graphical elements for a game of chance for a gaming machine using a graphics-based artificial game design system based upon machine learning training including analysis of past game performance, from other previously deployed games of chance wherein game of chance development occurs prior to: (i) a first submission of the game of chance to an independent testing laboratory for approval or certification; or (ii) allowing play of the game of chance for real-money play in a regulated gaming environment following approval or certification by the independent testing laboratory, and input past game performance using tiered scales based on importance; and
an artificial general intelligence foundational model and universal translator including at least an input mechanism, and media encoding and transcoding router to (i) change input data type to a different media format or consolidate the input data type to a specific file type and (ii) direct the changed or consolidated input data type to a specific neural network in a transformer process and select an output with a highest probability variable, wherein the artificial general intelligence foundational model and universal translator is configured to develop its own goal-seeking and reward behavior, gather and/or create training data in real-time, institute its own guardrails and optimization networks, and learn by feeding its output back into the input mechanism to develop the executable instructions or computer readable files related to graphical elements for a game of chance for a gaming machine;
wherein the at least portion developed executable instructions or computer readable files are used to present and allow play of the game of chance with the graphical elements on the gaming machine, the gaming machine including at least one of a monetary input device configured to receive a physical item associated with a monetary value and cashless wagering, a user interface, at least one processor for running the at least partially developed executable instructions or computer readable files related to the graphical elements for the game of chance for a gaming machine, a game display and memory in communication with the at least one processor.
15 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system utilizes at least partially supervised machine learning training to at least partially develop graphical elements for the game of chance.
16 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system includes at least a graphics-based game design system module utilizing at least partially supervised machine learning training to at least partially develop executable instructions or computer readable files.
17 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system includes at least a past game performance analytics module utilizing at least partially supervised machine learning training.
18 . The gaming system of any of claim 14, 15, 16 or 17 wherein the at least partially developed executable instructions or computer readable files related to graphical elements for the game of chance for a gaming machine utilize at least partially supervised machine learning training and are configured to develop a graphic of at least one of a game character, a reel set, game symbols, free symbols, a game background, a game logo, a game progressive box, a game credit bar, a secondary game character, or a game persistence graphic.
19 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system utilizes at least partially unsupervised machine learning training to at least partially develop graphical elements for the game of chance.
20 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system includes at least a graphics-based artificial intelligence game design system module utilizing at least partially unsupervised machine learning training to at least partially develop executable instructions or computer readable files.
21 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system includes at least a past game performance analytics module utilizing at least partially unsupervised machine learning training.
22 . The gaming system of any of claim 14, 19, 20 or 21 wherein the at least partially developed executable instructions or computer readable files related to graphical elements for the game of chance for a gaming machine utilize at least partially unsupervised machine learning training and are configured to develop a graphic of at least one of a game character, a reel set, game symbols, free symbols, a game background, a game logo, a game progressive box, a game credit bar, a secondary game character, or a game persistence graphic.
23 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system utilizes at least partially reinforced machine learning training to at least partially develop graphical elements for the game of chance.
24 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system includes at least a graphics-based artificial intelligence game design system module utilizes at least partially reinforced machine learning training to at least partially develop executable instructions or computer readable files.
25 . The gaming system of claim 14 wherein the graphics-based artificial intelligence game design system includes at least a past game performance analytics module utilizing at least partially reinforced machine learning training.
26 . The gaming system of any of claim 14, 23, 24 or 25 wherein the at least partially developed executable instructions or computer readable files related to graphical elements for the game of chance for the gaming machine utilizing at least partially reinforced machine learning training and includes developing a graphic of at least one of a game character, a reel set, game symbols, free symbols, a game background, a game logo, a game progressive box, a game credit bar, a secondary game character, or a game persistence graphic.