Thomas Schiex – författare

Artificial Intelligence (AI) is a central topic in contemporary computer science; one which has enabled many groundbreaking developments that have significantly influenced our society. Not only has it proved to be of fundamental importance in areas such as medicine, biology, economics, philosophy, linguistics, psychology and engineering, but it has also had a significant impact in a number of fields, including e-commerce, tourism, e-government, national security, manufacturing and other economic sectors. This book contains the proceedings of PAIS 2022, the 11th Conference on Prestigious Applications of Artificial Intelligence, held in Vienna, Austria, on 25 July 2022 as a satellite event of IJCAI-ECAI 2022. The PAIS conference invites papers describing innovative applications of AI techniques to real-world systems and problems, and aims to provide a forum for academic and industrial researchers and practitioners to share their experience and insight on the applicability, development and deployment of intelligent systems. A total of 18 full-paper submissions and 4 extended-abstract submissions were received for the 2022 conference, of which 10 full papers and 3 extended abstracts were accepted after rigorous peer review. The topics covered range from autonomous navigation, air traffic control and satellite management to the optimization of industrial processes and human-in-the-loop applications.The book will be of interest to all those whose work involves the innovative application of AI techniques to real-world situations.

Numerous formalisms have been designed to model and solve decision-making problems. Some formalisms, such as constraint networks, can express "simple" decision problems, while others take into account uncertainties (probabilities, possibilities...), unfeasible decisions, and utilities (additive or not). In the first part of this book, we introduce a generic algebraic framework that encompasses and unifies a large number of such formalisms. This formalism, called the Plausibility–Feasibility–Utility (PFU) framework, is based on algebraic structures, graphical models, and sequences of quantifications. This work on knowledge representation is completed by a work on algorithms for answering queries formulated in the PFU framework. The algorithms defined are based on variable elimination or tree search, and work on a new generic architecture for local computations called multi-operator cluster DAGs.

This book constitutes the proceedings of the 25th International Conference on Principles and Practice of Constraint Programming, CP 2019, held in Stamford, CT, USA, France, in September/October 2019.The 44 full papers presented in this volume were carefully reviewed and selected from 118 submissions. They deal with all aspects of computing with constraints including theory, algorithms, environments, languages, models, systems, and applications such as decision making, resource allocation, scheduling, configuration, and planning. The papers were organized according to the following topics/tracks: technical track; application track; multi-agent and parallel CP track; testing and verification track; CP and data science track; computational sustainability; and CP and life sciences track.