Goal-directed Markov Decision Process models (GDMDPs) are good models for many decision-theoretic planning tasks. They have been used in conjunction with two different reward stru...
We study decision-theoretic planning or reinforcement learning in the presence of traps such as steep slopes for outdoor robots or staircases for indoor robots. In this case, achi...
We study how to find plans that maximize the expected total utility for a given MDP, a planning objective that is important for decision making in high-stakes domains. The optimal...
We consider the problem of representing plans for mixed-initiative planning, where several participants cooperate to develop plans. We claim that in such an environment, a crucial...
— Autonomous service robots have to recognize and interpret their environment to be able to interact with it. This paper will focus on service tasks such as serving a glass of wa...
Franziska Zacharias, Christoph Borst, Gerd Hirzing...