Conference: The 11th Pacific Rim International Conference on Artificial Intelligence (PRICAI2010) ====================================================================================== Special Session on Recent Advances in Multi-strategy Learning Systems applied to Machine Vision, Robotics and Control Paper deadline: March 31, 2010 URL: Multi-strategy learning systems integrate two or more inference types and/or representational mechanisms. These systems take advantage of the strengths of individual learning strategies, and therefore can be applied to a wider range of problems. Human learning is clearly not limited to any single strategy, but can involve any type of strategy, or a combination of them, depending on the task at hand. Research on multi-strategy learning is therefore a key to understanding learning processes in general, to making progress in machine learning, as well as to extending the applicability of current machine learning methods to new practical domains. This special session aims to provide an opportunity for international researchers to share and review recent advances in the foundations, integration architectures and applications of multi-strategy learning for computer vision and robot control. Authors are invited to submit their original and unpublished work in the areas including (but not limited to) the following: - Machine Vision: Object Recognition; Object Detection and Categorisation; Motion and Tracking; Video Analysis and Event Recognition; Biologically-inspired Vision and Face and Gesture Analysis - Robotics: Humanoid and Mobile Robotics; Bio-robotics; Tele-robotics; Service Robotics - Control: Cooperative control; Hybrid Intelligence Control; Adaptive Control; Robust Control and Networked Control System Special Session Organisers: Chee Seng Chan (Mimos Berhad, Malaysia) Napoleon Reyes (Massey University, New Zealand) Naoyuki Kubota (Tokyo Metropolitan University, Japan)