The Second World Congress on Nature and Biologically Inspired Computing (NaBIC2010) was held at the Kitakyushu International Conference Center December 15-17, 2010, in Kitakyushu, Japan. NaBIC2010 provided a forum for researchers, engineers, and students from worldwide to discuss state-of-the-art machine intelligence and to address issues related to building human-friendly machines by learning from nature.

NaBIC2010 covered a wide range of studies ? from theoretical and algorithmic studies on nature and biologically inspired computing techniques to their real-world applications.

Top researchers presenting papers at NaBIC2010 were invited to contribute to this special issue. Through a fair peer review process, four extended papers have been accepted ? an acceptance rate of 50%.

The first paper entitled gA Study on Computational Efficiency and Plasticity in Baldwinian Learningh by Liu and Iba analyzes Baldwinian evolution efficiency by comparing it to alternatives such as standard Darwinian evolution with no learning, Lamarckian evolution, and Baldwinian evolution with different learning and plasticity evolution.

The second paper entitled gExperimental Study of a Structured Differential Evolution with Mixed Strategiesh by Ishimizu and Tagawa proposes island-based DE with ring or torus networks. The authors examine the performance of the proposed DE with the effects of different strategies.

The third paper entitled gMulti-Space Competitive DGA for Model Selection and its Application to Localization of Multiple Signal Sourcesh by Ishikawa, Misawa, Kubota, Tokiwa, Horio, and Yamakawa proposes a distributed genetic algorithm in which each subpopulation searches for a solution in different decision space. Subpopulations change size based on search progress.

The fourth paper entitled gAn Extended Interactive Evolutionary Computation Using Heart Rate Variability as Fitness Value for Composing Music Chord Progressh by Fukumoto, Nakashima, Ogawa, and Imai uses heart-rate variability instead of direct human evaluations in an interactive evolutionary computation framework.

As guest editors of this special issue, we would like to thank the authors for their unique and interesting contributions and the reviewers for their careful checking and invaluable comments.