TPNC 2016 - 5th International Conference on the Theory and Practice of Natural Computing

TPNC is a conference series intending to cover the wide spectrum of computational principles, models and techniques inspired by information processing in nature. TPNC 2016 will reserve significant room for young scholars at the beginning of their career and particular focus will be put on methodology. The conference aims at attracting contributions to nature-inspired models of computation, synthesizing nature by means of computation, nature-inspired materials, and information processing in nature.
Venue
TPNC 2016 will take place in Sendai, in the northeast (Tohoku) region of Japan. The city was founded in 1600 and is nicknamed the "city of trees". It is the second largest city north of Tokyo. It takes about 100 minutes to reach Sendai from Tokyo by bullet train (Shinkansen). The venue will be the Cyberscience Center, Aobayama Campus, Tohoku University:
Scope
Topics include, but are not limited to:
Theoretical contributions to
amorphous computing
ant colonies
artificial chemistry
artificial immune systems
artificial life
bacterial foraging
cellular automata
chaos computing
collision-based computing
complex adaptive systems
computing with DNA
computing with words and perceptions
developmental systems
evolutionary computing
fractal geometry
fuzzy logic
gene assembly in ciliates
granular computing
intelligent systems
in-vivo computing
membrane computing
nanocomputing
neural computing
optical computing
physarum machines
quantum computing
quantum information
reaction-diffusion systems
rough sets
self-organizing systems
swarm intelligence
synthetic biology
Applications of natural computing to
algorithmics
bioinformatics
control
cryptography
design
economics
graphics
hardware
human-computer interaction
knowledge discovery
learning
logistics
medicine
natural language processing
optimization
pattern recognition
planning and scheduling
programming
robotics
telecommunications
web intelligence
A flexible "theory to/from practice" approach would be the perfect focus for the expected contributions.