As quantum information and computation research continues to develop, we will see increasing interest in adapting the philosophy of quantum computing, information theory and ideology into other, more traditional aspects of computational research. Although the hardware technology to realize quantum computing still yet to be materialized, research about the theoretical aspects of quantum computing and its ideology has enjoyed some success with artificial and computational intelligence.

This special session focus on combining various aspects of quantum computing, information theory, and other aspects with existing fields in artificial intelligence, especially evolutionary computation. For example, quantum computing has inspired ideas in evolutionary algorithms. Quantum probability is important because probability is inherently used in evolutionary and other stochastic algorithms. Quantum entanglement can further revolutionize the above algorithmic approaches. Quantum information theory also has great potential as many research have correlated information theory with evolution. Quantum complexity theory is also closely related to algorithm complexity.

Details can be found in our website:

http://web.cecs.pdx.edu/~whung/cec2012/