AI for Service Composition In the last years, there has been increasing interest in service composition. The key idea is that existing distributed services can be selected and combined into suitable workflows of tasks, in order to provide new functionalities or appli- cations. Service composition has the potentiality to revolutionize the classical approaches to data integration and business process integration, reducing devel- opment time and effort. Standards and platforms based on service models and supporting service composition have been developed in different frameworks, including web services, grid services, and agent services. AI techniques have been used to support different key aspects of the man- agement of service compositions, including tasks such as their generation, allo- cation of resources, execution, monitoring and repair. For instance, knowledge representation techniques have been exploited to provide suitable semantic an- notations of services; planning has been applied to an automatic generation of the workflows composing the services; scheduling has been applied to resource allocation and workflow optimization; and agent techniques have been applied to support a dynamic adaptation of the workflows. However, many issues remain to be resolved. These include (1) forming pre- cise, clean and general characterizations of service compositions, and identifying the most appropriate ways to formalize the critical steps in their life cycle; (2) determining suitable languages to represent service compositions in all their rel- evant aspects and finding ways of bridging the gap between service composition languages used in the industry and languages exploited in AI; (3) highlight- ing important challenges for AI to be effective in practical, industrial contexts, proposing techniques and tools able to address these challenges in realistic sce- narios, and finding architectures for integrating such techniques in a robust, integrated environment. The 8 full papers and 4 short papers appearing in this proceedings address these and other relevant problems in service composition. This workshop has been organized under the MIUR-FIRB project RBNE0195K5 ”Knowledge Level Automated Software Engineering”. It is the continuation of three successful workshops at ICAPS 2003, ICAPS 2004, and AAAI 2005, and aims at becoming a regular meeting place for researcher and practitioners working in the field of AI and in the area of service composition. Marco Pistore Jose Luis Ambite Jim Blythe Jana Koehler Sheila McIlraith Biplav Srivastava August 28, 2006 i