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The paper presents an integrated approach for automated semantic web service composition using AI planning techniques. An important advantage of this approach is that the composition process, as well as the discovery of the atomic services that take part in the composition, are significantly facilitated by the incorporation of semantic information. OWL-S web service descriptions are transformed into a planning problem described in a standardized fashion using PDDL, while semantic information is used for the enhancement of the composition process as well as for approximating the optimal composite service when exact solutions are not found. Solving, visualization, manipulation, and evaluation of the produced composite services are accomplished, while, unlike other systems, independence from specific planners is maintained. Implementation was performed through the development and integration of two software systems, namely PORSCE II and VLEPPO. PORSCE II is responsible for the transformation process, semantic enhancement, and management of the results. VLEPPO is a general-purpose planning system used to automatically acquire solutions for the problem by invoking external planners. A case study is also presented to demonstrate the functionality, performance, and potential of the approach.