The first Workshop on Quantum artificial Intelligence aims to bring together scientists from the areas of quantum computer science and artificial intelligence to lay the groundwork for defining theories, methodologies and applications of quantum artificial intelligence.
The workshop is intended to be a brainstorming session in which computer scientists, mathematicians, physicists and engineers will interact to clarify and develop new ideas about quantum intelligent machines. Thinking about new neural models based on quantum phenomena, designing new optimization schemes that can exploit the inherent parallelism of quantum computation, introducing reasoning methodologies based on quantum schemes that can emulate human thinking. The discussions and presentations given at the Workshop will go into the details of the above topics and enable participants to enhance their skills in this pioneering field of research. Like the famous 1956 Darthmouth workshop, the 2023 Naples workshop will break new ground in computer science research and define entirely new paths for the design and implementation of efficient algorithms for artificial intelligence.
As an important side effect, the Workshop will enable the embryonic core network of researchers acting in the field of quantum artificial intelligence that will constitute the IEEE Computer Society Technical Community on Quantum Artificial Intelligence.
High-quality research presented at the Workshop will be offered submission and review for publication in a special issue of Springer Quantum Machine Intelligence.
This workshop is supported by the Emerging Technology Award of the IEEE Computer Society obtained by Prof. Giovanni Acampora and Dr. Autilia Vitiello in 2022.
Accepted short papers will be collected in informal proceedings that will be distributed at the workshop. After the workshop, authors of original contributions will be invited to submit an extended version of their abstracts to the Quantum Machine Intelligence journal.
Example topics include, but are not limited to