Publications

During the last three decades, the field of Intelligent and Evolutionary Systems (IES) has established itself as a key research area, with the ability to address common problems across diverse disciplines. Many challenges arise from the massive volumes of data provided by widespread automation, and from the increasingly complex webs of interaction that arise as local events scale up to generate global phenomena. Inspiration from biology – the core concept of IES research - underlies key advances in engineering systems that respond with adaptive intelligence and resilience in such noisy, dynamic environments.

Today, IES continues to develop, as traditional neural and genetic computation techniques are supplemented with new ideas from a diverse range of areas that include swarm computing, artificial life, complex systems and many others. Advances on key theoretical fronts are complemented by close ties to applications within specific areas, ensuring that IES retain relevance across disciplines.

The Asia Pacific Symposium on Intelligent and Evolutionary Systems is an annual event that brings together researchers from the Asia-Pacific Rim and other areas to discuss emerging ideas as well as on-going research in intelligent and evolutionary computation, and to deepen and extend links and collaboration in the community.

The 2008 event is the 12th meeting in a series of IES symposia that originated in 1997. This year, the event was held in Melbourne, Australia in conjunction with the 7th International Conference on Simulated Evolution and Learning (SEAL'08). The work presented at the symposium is indicative of the diverse areas touched by IES research, with applications in architecture, horticulture, epidemiology, software development and traffic control among others. In addition to exploring several new applications of genetic algorithms, papers here develop novel approaches to data assimilation, examine the theory and application of learning systems, and explore the evolution of culture and cooperation in multi-agent simulations. Key ideas such as non-dominance and entropy evolution are also further developed.

We are very grateful to the many people who have helped to make this year's symposium a success. First of all we thank the authors for their work and participation, and for providing manuscripts on time and in a standard format. All papers were carefully reviewed by at least two independent members of the program committee to ensure quality and consistency, and the time and effort contributed by the program committee are much appreciated. We are particularly grateful to Prof. David Green whose experience from previous IES meetings was invaluable for ensuring the success of this year's event. We also thank Ms Dianne Nguyen for her assistance with the event coordination and the production of these proceedings.

Premature convergence is a persisting problem in evolutionary optimisation, in particular – genetic algorithms. While a number of methods exist to approach this issue, they usually require problem specific calibration or only partially resolve the issue, at best by delaying the premature convergence of an evolving population. Analytical models in biology show that resiliently diverse populations evolve on high-dimensional fitness landscapes with “holey” rather than “rugged” topographies, but the implications for artificial evolutionary systems remain largely unexplored. Here I show how holey fitness landscapes (HFLs) can be incorporated in an evolutionary algorithm and use this approach to investigate the ability of HFLs to maintain genetic diversity in an evolving population. The results indicate that an underlying HFL can counteract premature genetic convergence and sustain diversity. They also suggest that HFL may provide a flexible mechanism for dynamic creation and maintenance of subpopulations that concentrate their evolutionary search in different regions of the solution space. Finally, I discuss on-going work on using the HFL model in optimisation problems.