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AI planning constitutes a field of interest as its techniques can be applied to many areas. Contemporary systems that are being developed deal with certain aspects of planning and mainly focused on dealing with advanced features such as resources, time and numerical expressions. This paper presents VLEPpO, a Visual Language for Enhanced Planning pr...
Contexts in source publication
Context 1
... Gripper domain has four relations, as depicted in Figure 2: a) at-robot, which specifies the position of the robot and it is connected only with one instance of room, b) at which specifies the room in which each ball resides and therefore is connected with an instance of ball and an instance of room, c) holding which defines the alternative position of a ball, i.e. it is held by the robot and therefore it is connected with an instance of ball and an instance of gripper and d) empty which is connected only with an instance of gripper and states that the current gripper does not hold any ball. Note here that although non-typed PDDL requires only the arity for each predicate and not the type of objects for the arguments, the interface obliges the user to connect each predicate with specific object classes and this is used for the consistency check of the domain design. ...
Context 2
... here that although non-typed PDDL requires only the arity for each predicate and not the type of objects for the arguments, the interface obliges the user to connect each predicate with specific object classes and this is used for the consistency check of the domain design. According to the design of Figure 2, the arity of predicate holding, for example, is two and the specific predicate can only be connected with one object of class ball and one object of class gripper. ...
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Citations
... All web service related steps, namely transformation, semantic enhancement, service accuracy assessment, service replacement and reverse transformation, are implemented in the PORSCE II system [1]. Planning related steps are accommodated by the VLEPPO system [2] [24], which can also be used as a general purpose planning system for other applications. Implementation of these steps in the two systems is depicted in Fig. 1. ...
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.
... Another goal concerns the exploration of the possibility to accelerate the composition process by asserting the produced OWL- S profiles in the base of the available atomic services. Finally, integration with VLEPPO [4] is a promising direction for visual design of web service composition. ...
PORSCE II is a framework that performs automatic web service composition by transforming the composition problem into AI planning
terms and utilizing external planners to obtain solutions. A distinctive feature of the system is that throughout the entire
process, it achieves semantic awareness by exploiting semantic information extracted from the OWL-S descriptions of the available
atomic web services and the corresponding ontologies. This information is then used in order to enhance the planning domain
and problem. Semantic awareness facilitates approximations when searching for suitable atomic services, as well as modification
of the produced composite service. The alternatives for modification include the replacement of a certain atomic service that
takes part in the composite service by an equivalent or a semantically relevant service, the replacement of an atomic service
through planning, or the replanning from a certain point in the composite service. The system also provides semantic representation
of the produced composite service.
... In addition, another future goal concerns the exploration of the possibility to accelerate the composition process by asserting the produced OWL-S profiles in the base of the available web services, under certain time constraints. Furthermore, integration with the VLEPPO system (Hatzi et al., 2007) is a promising future direction, in order to accommodate design and solving of the web service composition problems. Finally, it lies in our immediate plans to study ways to enhance the services representation and explore the ability to produce various composite services according to non-functional properties. ...
This paper presents PORSCE II, an integrated system that performs automatic semantic web service composition exploiting AI techniques, specifically planning. Essential steps in achieving web service composition include the translation of the web service composition problem into a solver-ready planning domain and problem, followed by the acquisition of solutions, and the translation of the solutions back to web service terms. The solutions to the problem, that is, the descriptions of the desired composite service, are obtained by means of external domain-independent planning systems, they are visualized and finally evaluated. Throughout the entire process, the system exploits semantic information extracted from the semantic descriptions of the available web services and the corresponding ontologies, in order to perform composition under semantic awareness and relaxation.
... In addition, another goal concerns incorporating the quality distance metric with plan statistics in a common metric. Furthermore, integration with the VLEPPO system [9] is a promising future direction, in order to accommodate design and solving of the web service composition problems. Finally, it lies in our immediate plans to study ways to enhance the services representation and explore the ability to produce various complex services according to non-functional properties. ...
This paper presents PORSCE II, an integrated system that performs automatic semantic web service composition through planning. In order to achieve that, an essential step is the translation of the web service composition problem into a planning problem. The planning problem is then solved using external domain-independent planning systems, and the solutions are visualized and evaluated. The system exploits semantic information to enhance the translation and planning processes.
... Future goals include the extension of the system in order to translate the plan describing the complex service into OWL-S for consequent execution and automatic feedback. Furthermore, integration with the VLEPPO system [9] is a promising future direction, in order to accommodate visual design and solving of web service composition problems as planning problems. Finally, it lies in our immediate plans to study ways to enhance the services representation and explore the ability to produce various complex services according to non-functional user preferences, such as Quality of Service (QoS), resource and time constraints. ...
This paper presents PORSCE II, a system that combines planning and ontology concept relevance for automatically composing semantic web services. The presented approach includes transformation of the web service composition problem into a planning problem, enhancement with semantic awareness and relaxation and solution through external planners. The produced plans are visualized and their accuracy is assessed.
AI planning is the field that focuses on creating abstract representations of various processes. As such, it is obvious that it is a broad field and demands specialized tools to be used in order to ease the process of designing domains and problems. The literature shows that most of these tools do not offer an option to re-examine and validate the result of the aforementioned designing process.
This work presents a novel approach to validating a description of a problem as well as presenting information related to this validation process in an efficient way. It introduces a proxy web service that implements the process of finding invalid descriptions as well as the extension of the relevant tool VLEPpO, that suited the needs of the visualization process.
Although new AI planning algorithms and techniques are being developed and improved rapidly, there is a lack of efficient and easy to use systems able to incorporate and utilize them. Furthermore, while visual representation facilitates design, maintenance and comprehension of planning domains and problems, very few systems incorporate it. This paper presents VLEPPO, an integrated system aiming at visually modeling planning domains and problems through a convenient graphical interface, while maintaining compatibility with the Planning Domain Definition Language (PDDL), with import and export features. Solutions to planning problems can be obtained by invoking different planners employing the web services technology. The demonstration of the system is performed through a case study involving web service composition viewed as a planning problem.
