Featured Project
## Problem
Due to the severe pandemic of COVID-19, people around the world have to keep a safe social distance and to avoid big parties. As one of famous Poker games in the western world, the Texas Hold’em is also influenced by the pandemic and tends to turn to online game platform, which, unfortunately, brings much less real excites and fun to its players. We hope to develop a product to assist Poker players to get rid of the limit of time and space, trying to let them enjoy card games just as before the pandemic.
## Solution Overview
Our solution is to develop an Intelligent Texas Hold’em robot, which can make decisions in real Texas poker games. The robot is expected to play as an independent real player and make decisions in game. It means the robot should be capable of getting the information of public cards and hole cards and making the best possible decisions for betting to get as many chips as possible.
## Solution Components
-A Decision Model Based on Multilayer Neural Network
-A Texas Hold'em simulation model which based on traditional probabilistic models used for generating training data which are used for training the decision model
-A module of computer vision enabling game AI to recognize different faces and suits of cards and to identify the game situation on the table.
-A manipulation robot hand which is able to pick, hold and rotate cards.
-Several Cameras helping to movement of robot hand and the location of cards.
## Criterion for Success
- Training a decision model for betting using deep learning techniques (mainly reinforcement learning).
- Using cv technology to transform the information of public cards and hole cards and the chips of other players to valid input to the decision-making model.
- Using speech recognition technology to recognize other players’ actions for betting as valid input to the decision model.
Using the PTZ to realize the movement of the cameras which are used to capture the information of pokers and chips.
- Finish the mechanical design of an interactive robot, which includes actions like draw cards, move cards to camera, move chips and so on. Utilize MCU to control the robot.
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