Combining Artificial Intelligence and Mathematical Analysis
There is no need to argue the relevance of AI in today’s world. Indeed, over the last couple of years Artificial Intelligence (AI) has drawn an enormous amount of world‐wide attention throughout society. It has captured the public imagination, academic attention, and attracted large business investments. This attention is for a substantial part triggered by the success that several AI applications have obtained in recent years, amongst others in image recognition, natural language processing, game playing (computer games, Go), handwriting transcription, and image‐based medical diagnosis.
Mathematical analysis and decision-making on the other hand has had a tremendous amount of success over the past several decades in helping to understand and solve a broad range of fundamental and business problems, ranging from transportation problems to workforce scheduling problems, from manufacturing problems to radiology problems, and from investment portfolio problems to inventory problems.
The combination of these two fields leads to Mathematics of Cooperative AI, a relatively young research field with many important unanswered questions, where the goal is to develop a general theory for making effective and intelligent joint decisions. It is precisely this field that Baarslag will focus his efforts on. As he himself puts it: “In this appointment, my goal is to act as a bridge between Mathematics and Cooperative AI, by developing a foundational theory for making effective and intelligent joint decisions".
