Synopses & Reviews
Computing and science reveal a synergic relationship. On the one hand, it is widely evident that computing plays an important role in the scientific endeavor. On the other hand, the role of scientific method in computing is getting increasingly important, especially in providing ways to experimentally evaluate the properties of complex computing systems. This book critically presents these issues from a unitary conceptual and methodological perspective by addressing specific case studies at the intersection between computing and science. The book originates from, and collects the experience of, a course for PhD students in Information Engineering held at the Politecnico di Milano. Following the structure of the course, the book features contributions from some researchers who are working at the intersection between computing and science.
About the Author
Francesco Amigoni (in 1999 a visiting scholar at the Computer Science Department of the Stanford University (USA), is an associate professor at the Department of Elettronics and Information of the Politecnico di Milano. His main research interests include: agents and multiagent systems, mobile robotics, and the philosophical aspects of artificial intelligence. Viola Schiaffonati (a visiting scholar at the Department of Philosophy of the University of California at Berkeley in 2000 and visiting researcher at the Suppes Center for the Interdisciplinary Study of Science and Technology of the Stanford University in 2005), is a temporary researcher at the Department of Elettronics and Information of the Politecnico di Milano and contract professor in the Faculty of Information Engineering of the Politecnico di Milano. Her main research interests include: foundational issues of artificial intelligence, formal approaches to the philosophy of science, and epistemological issues of computational science.
Table of Contents
How far chemistry and toxicology are computational sciences?.- Computational models for environmental systems.- Good experimental methodologies for autonomous robotics: from theory to practice.- Robotics benchmarking from the inside, i.e., the RAWSEEDS experience.- Artificial Intelligence and the explanation of intelligent behavior: methodological problems.