VIDEO & INTRODUCTION
Today's decision makers in fields ranging from engineering to psychology to medicine to economics to homeland security are faced with remarkable new technologies, huge amounts of information to help them in reaching good decisions, and the ability to share information at unprecedented speeds and quantities. These tools and resources should lead to better decisions. Yet, the tools bring with them daunting new problems: the massive amounts of data available are often incomplete or unreliable or distributed and there is great uncertainty in them; interoperating/distributed decision makers and decision making devices need to be coordinated; many sources of data need to be fused into a good decision; information sharing under new cooperation/competition arrangementsraises security problems. When faced with such issues, there are few highly efficient algorithms available to support decisions. This Action's objective is to improve the ability of decision makers to perform in the face of these new challenges and problems through the use of methods of theoretical computer science, in particular algorithmic methods. The primary goal of the project is to explore and develop algorithmic approaches to decision problems arising in a variety of applications areas. Since many of the decision problems investigated arise in Artificial Intelligence, an important sub-goal is to explore the cross-fertilisation of Decision Theory and Artificial Intelligence.
Examples of such mutual benefits include, but are not limited to:
This site contains materials originating from the tutorials and courses who took place at the meetings and doctoral schools organised by the COST Action IC0602 Algorithmic Decision Theory. It will be further updated as new materials will be produced by the COST Action.