Special Issue in Computational Aspects Related to Unconventional, Bioinspired and Quantum Methods

The following special issue, of which we are the guest editors will be published in “Computation” (ISSN 2079-3197, http://www.mdpi.com/journal/computation), and is now open to receive submissions of full research articles and comprehensive review papers for peer-review and possible publication.

Special Issue: Computational Aspects Related to Unconventional, Bio-Inspired and Quantum Methods

Website: http://www.mdpi.com/journal/computation/special_issues/computational_aspects

Guest Editors: Dr. Theodore Andronikos, Dr. Dimitrios Tsoumakos, Dr. Spyros Sioutas, Dr. Ioannis Panagis and Dr. Konstantinos Giannakis

Deadline for manuscript submissions: 31 January 2017

Given your interesting work on the theme and related disciplines, we personally invite you and your colleagues to submit a contribution for this special issue in which some of the leading experts will describe their work, ideas and findings.

Authors can take advantage of benefits including: Open Access; No Copyright Constraints; Rapid publication; Thorough Peer-Review; No Space Constraints, No Extra Space or Color Charges; Low Fees (350 CHF).

Please also note if your paper is submitted before 1 January 2017, it will be free of charge. Keywords

natural computing
quantum computing
quantum and quantum-inspired algorithms
molecular and DNA computing
chemical computing
molecular machines incorporating information processing
membrane computing
neural networks
evolutionary computing
computation graphs
computation on networks and graphs
computing based on dynamical systems
non-standard approaches
fuzzy computing
computation approaches going beyond the Turing model
application of non-standard computational methods
physics of computation
non-traditional approaches to classical problems
parallel computing
algorithms based on ant colonies, bees foraging etc.
logics of unconventional computing
physical limits to mechanical computation
unconventional methods in education and learning approaches

This special issue is supported by the research group QUIT affiliated with the Dept. of Informatics of the Ionian University. QUIT’s website: http://quit.di.ionio.gr/