Regulation for artificial intelligence and robotics in transportation, logistics and supply chain management

[1]  Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles , 2022 .

[2]  Giuseppe Contissa,et al.  Design According to Liabilities: ACAS X and the Treatment of ADS-B Position Data , 2015 .

[3]  Giuseppe Contissa,et al.  Liability and automation : issues and challenges for socio-technical systems , 2013 .

[4]  Luca Save,et al.  Designing Human-Automation Interaction : a new level of Automation Taxonomy , 2013 .

[5]  John A. Stankovic,et al.  Research Directions for the Internet of Things , 2014, IEEE Internet of Things Journal.

[6]  Drew McDermott,et al.  Introduction to artificial intelligence , 1986, Addison-Wesley series in computer science.

[7]  Mauro Gamberi,et al.  Automatic assessment of the ergonomic risk for manual manufacturing and assembly activities through optical motion capture technology , 2018 .

[8]  Raymond Kurzweil,et al.  Age of intelligent machines , 1990 .

[9]  Randy Goebel,et al.  Computational intelligence - a logical approach , 1998 .

[10]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[11]  Gert Brüggemeier.  Common Principles of Tort Law: A Pre-Statement of Law , 2004 .

[12]  Maurizio Faccio,et al.  Assembly system design in the Industry 4.0 era: a general framework , 2017 .

[13]  George Chryssolouris,et al.  Assembly system design and operations for product variety , 2011 .

[14]  Ronald Azuma,et al.  Recent Advances in Augmented Reality , 2001, IEEE Computer Graphics and Applications.

[15]  Peter A. Flach,et al.  Machine Learning - The Art and Science of Algorithms that Make Sense of Data , 2012 .

[16]  Richard Ernest Bellman,et al.  An Introduction to Artificial Intelligence: Can Computers Think? , 1978 .

[17]  Wendy L. Tate,et al.  Offshoring and Reshoring: An Update on the Manufacturing Location Decision , 2013 .

[18]  Alberto Regattieri,et al.  On the use of machine learning methods to predict component reliability from data-driven industrial case studies , 2017, The International Journal of Advanced Manufacturing Technology.