Lack of sufficient semantic description makes it difficult to find and compose suitable Web services during analysis, search, and matching processes. As Semantic Web Services provide well-defined meaning, composition of new services is possible through logical deductions achieving resolutions automatically. This book develops an Inference-based Semantic Business Process Composition Agent (SCA). Utilizing Revised Armstrong's Axioms (RAAs) in inferring functional dependencies, SCA System composes available OWL-S based atomic processes into required services. RAAs are embedded in the knowledge base ontology of SCA System. In order to find functional dependencies between processes in the candidate set of SWSs, the Semantic Matching Step (SMS) was prepared using a well-organized matchmaking algorithm. The SMS scores the similarity of two focused-on processes based on the assessment of distance among concepts. Experiments show that the SCA System produces process sequences as a composition plan that satisfies user's requirement for a complex task. The SCA System is the first to use RAAs for semantic-based planning and inference.