Automated Planning and Acting

Malik Ghallab is a Research Director at the Centre National de la Recherche Scientifique (CNRS), Paris. For most of his career he has been with LAAS-CNRS, University of Toulouse. His research activity is mainly focused on planning, acting and learning in robotics and AI. He has co-authored several books and more than two hundred scientific publications. He has been head of a French research program in Robotics, director of LAAS-CNRS and CEO for Research and Technology of INRIA. He is a Fellow of the European Coordinating Committee for Artificial Intelligence. Dana Nau is a Professor at the University of Maryland, in the Department of Computer Science and the Institute for Systems Research. He has more than 300 refereed technical publications. Some of his best-known research contributions include the discovery of pathological game trees, the strategic planning algorithm that Bridge Baron used to win the 1997 world championship of computer bridge, applications of AI in automated manufacturing, automated planning systems such as SHOP, SHOP2, and Pyhop, and evolutionary game-theoretic studies of cultural evolution. He is a fellow of the Association for the Advancement of Artificial Intelligence Fellow and the Association for Computer Machinery. Paolo Traverso is the Director of FBK ICT-IRST, the Center for Information and Communication Technology at Fondazione Bruno Kessler, part of the European Institution of Innovation and Technology, whose goal is to foster innovation and impact on market and society. Paolo has worked in the advanced technology groups of management information consulting companies in Chicago, London, and Milan, leading projects in safety critical systems, data and knowledge management, and service oriented applications. He has published more than one hundred papers in artificial intelligence, automated planning and service oriented computing. He is a Fellow of the European Coordinating Committee for Artificial Intelligence.

1. Introduction; 2. Deliberation with deterministic models; 3. Deliberation with refinement methods; 4. Deliberation with temporal models; 5. Deliberation with nondeterministic models; 6. Deliberation with probabilistic models; 7. Other deliberation functions; 8. Concluding remarks.