Abstract. Factored Markov Decision Processes is the theoretical framework underlying multi-step Learning Classifier Systems research. This framework is mostly used in the context ...
Abstract— Knowledge of the driving environment is essential for robotic vehicles to comply with traffic rules while autonomously traversing intersections. However, due to limite...
Many complex real-world decision problems, such as planning, contain an underlying constraint reasoning problem. The feasibility of a solution candidate then depends on the consis...
—Constraint satisfaction has been a very successful paradigm for solving problems such as resource allocation and planning. Many of these problems pose themselves in a context in...
Abstract. We introduce a new theoretical model of ad hoc mobile computing in which agents have severely restricted memory, highly unpredictable movement and no initial knowledge of...