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Quadropoly Academy - Data Science for Board Game Gameplay, Trailers and Related Videos

About the application:

This is a Classic Property Trading Mini game with hundreds customisation options supercharged with Artificial Intelligence trained on true mini games with professional users. Download and enroll into Quadropoly Academy today! With this Classic Property Trading Mini game you will be able to learn how to play on professional level and compete in International Tournaments by playing with state of the art AI trained with Machine Learning. Special and exclusive AI Tip feature would tutorial you through your learning adventure. With Roll Your Own Dice feature you will see the champion is decided not by the Dice and luck, but your skill and strategy. Artificial Intelligence in Quadropoly has been training on a vast collection of true mini games for 2.5 years and counting. AI becomes better with every user who should achieve at least 40% winrate on Monopolist or 30% on Winner difficulty levels. 🎯 First true Artificial Intelligence for Classic Business Board mini game, third after Deep Blue for Chess and AlphaGo for Go 📇 Help for all official guidelines by the ebook 🎻 Help for majority of house guidelines 🎓 AI tip at any moment in mini game to speed up your learning 🎭 Every single AI in every mini game is special and has its own personality which defines its risk taking or risk averse tendencies as well as the attitude towards property. AIs are good at imitating true people: they should be annoyed, desperate and greedy as well as 'feel' a range of another emotions 🎲 Optional External Dice feature 🌠 Variable mini game speed 💾 100% data integrity 🏆 Detailed Acc info with stats, custom built leaderboards and challenges 🆕 Frequent updates with fresh features: http://quadropoly.com.au/app-releases/ 📠 Full anonymous logs (5-8Kb per mini game) are uploaded to the Cloud for Machine Learning ❕ Learn about differences between AI levels through in-game help This is Academy: it has all AI levels with most Pro features accessible but supported by ads These are the main foundations this mini game has been built on: 🔵 No cheating. No re-rolls, every dice roll is final. No hidden luck parameters used by others, regardless of the difficulty. Pure data science for Machine Learning against your skill with guaranteed random dice rolls 🔵 No preferential (discriminatory) trading for AI. This is the second trick others use to lift the difficulty. In Quadropoly, AI does not know whether their trading partner is other AI or a human, regardless of the difficulty: trade offer evaluations depend on beautiful much everything on the board at the moment of trade, but not on who their enemy is This classic Board Mini game has been built by independent fanatics for people who appreciate real challenge of super clever AI instead of widely used cheats. The goal of this project is to prove data science should be a lot of fun! Unlike human enemy, AIs are infinitely patient, create their turn as quick as you tell them and never quit the mini game when you begin winning. Additionally, with AI tip system in Quadropoly you can rapidly improve your own skills in any Business Trading mini game, learn the true value of the properties, monopolies and cash, improve your negotiation skills, and, most importantly, avoid throwing (or dodging) mini game pieces at your enemies face. With 6 AI difficulty levels accessible you can always stop on a level you feel comfortable with, advancing at your own pace. With top level AI capable of participating in monopoly Championships, even the best users in the Globe are guaranteed to search the mini game very challenging yet 100% fair. If you would like to share your thoughts on what should be improved - please contact us at [email protected] If you like the mini game, please help our work by upgrading to Pro ver. You will receive larger board, no advertisements and another exclusive features: https://play.google.com/store/apps/details?id=au.com.quadropoly.monopoly Your progress will be preserved! Powered by Python, Kivy and Kivent