AI Open Day

Test your knowledge in a game like checkers against a robot that is programmed to predict the state of the gameboard for up to 9 moves ahead. You can experience the interaction with an industrial robot and compare your strength in checkers with the algorithms of artificial intelligence by choosing between three difficulty levels.

This robotic cell demonstrates how Artificial Intelligence, Computer Vision and collaborative robotics can be combined to develop an application of a Human-Robot Collaboration. 

It also shows that modern design approaches of industrial robots allow them to safely interact with humans, and thus can be used for teaching and education as well. The task of creating a collaborative robotic workplace for playing a game includes adjusting the input signals from the outside world using available devices, such as a camera, a touch screen, and sensors of the robot itself. Furthermore, it is necessary to consider the psychological perception of the game process by a human. When competing with a supposedly stronger robotic opponent, one would expect fast decision-making, conciseness of movements, and the impossibility of deception. Therefore, an implementation of the game algorithm should be robust enough to take little time while calculating an optimal move and complying with defined game rules.

The Sudoku Assistant is an AI assistant that can interpret, solve and explain pen-and-paper Sudokus scanned with a smartphone. It uses techniques from both machine learning and constraint programming, but goes one step further: it employs a new way of integrating digit recognition and reasoning more deeply, allowing it to solve significantly more scanned Sudokus correctly than previous approaches were able to.
Furthermore, it isn’t limited to merely solving Sudokus: through the use of our state-of-the-art research on step-wise explanations to constraint satisfaction problems, it is able to guide the user through the solving process by giving small hints. This ensures that the AI system doesn’t ruin the fun by doing the solving for you, but is able to assist you when you are stuck. The Sudoku Assistant hence demonstrates three concepts that are becoming increasingly important in AI research: the integration of learning and reasoning, explainable AI and human-centred AI. And although the assistant is focused on Sudoku, the underlying techniques are equally applicable to other constraint-solving problems like timetabling, scheduling and vehicle routing.