SSALMul 2013 - Special Session on Adaptive and Learning Multi-agent Systems

Multi-Agent Systems (MAS) have grown into an interdisciplinary field that includes various tracks and embraces many previously distinctive research areas. More and more MASs are situated in open and dynamic environments. The changes of environments that may be unpredictable, uncontrollable and evolving typically affect the MAS. Recently, adaptive MAS and MAS learning have become important sub-areas in the literature of MAS. Particularly, both of them investigate how multiple intelligent computational agents can work together to achieve high-level goals by adjusting themselves and obtaining more information. Various approaches have been applied to improve the adaptive and learning ability of MAS. MAS are still facing challenges of scaling to large numbers of entities and real-world tasks.
This special session on adaptive and learning multi-agent systems will provide a forum for researchers and practitioners interested in adaptation and learning for multi-agent systems, and report their latest findings.
For more information, see the special session web site http://nical.ustc.edu.cn/ideal13/ss_alms.html.