HTN planning: Overview, comparison, and beyond

Hierarchies are one of the most common structures used to understand and conceptualise the world. Within the field of Artificial Intelligence (AI) planning, which deals with the automation of world-relevant problems, Hierarchical Task Network (HTN) planning is the branch that represents and handles hierarchies. In particular, the requirement for rich domain knowledge to characterise the world enables HTN planning to be very useful, and also to perform well. However, the history of almost 40 years obfuscates the current understanding of HTN planning in terms of accomplishments, planning models, similarities and differences among hierarchical planners, and its current and objective image. On top of these issues, the ability of hierarchical planning to truly cope with the requirements of real-world applications has been often questioned. As a remedy, we propose a framework-based approach where we first provide a basis for defining different formal models of hierarchical planning, and define two models that comprise a large portion of HTN planners. Second, we provide a set of concepts that helps in interpreting HTN planners from the aspect of their search space. Then, we analyse and compare the planners based on a variety of properties organised in five segments, namely domain authoring, expressiveness, competence, computation and applicability. Furthermore, we select Web service composition as a real-world and current application, and classify and compare the approaches that employ HTN planning to solve the problem of service composition. Finally, we conclude with our findings and present directions for future work. In summary, we provide a novel and comprehensive viewpoint on a core AI planning technique.<br/

Software Reliability in Semantic Web Service Composition Applications

Web Service Composition allows the development of easily reconfigurable applications that can be quickly adapted to business changes. Due to the shift in paradigm from traditional systems, new approaches are needed in order to evaluate the reliability of web service composition applications. In this paper we present an approach based on intelligent agents for semiautomatic composition as well as methods for assessing reliability. Abstract web services, corresponding to a group of services that accomplishes a specific functionality are used as a mean of assuring better system reliability. The model can be extended with other Quality of Services – QoS attributes.Software Reliability, Web Service Composition, Intelligent Agents

Dynamic Web Services Composition

Emerging web services technology has introduced the concept of autonomic interoperability and portability between services. The number of online services has increased dramatically with many duplicating similar functionality and results. Composing online services to solve user needs is a growing area of research. This entails designing systems which can discover participating services and integrate these according to the end user requirements. This thesis proposes a Dynamic Web Services Composition (DWSC) process that is based upon consideration of previously successful attempts in this area, in particular utilizing AI-planning based solutions. It proposes a unique approach for service selection and dynamic web service composition by exploring the possibility of semantic web usability and its limitations. It also proposes a design architecture called Optimal Synthesis Plan Generation framework (OSPG), which supports the composition process through the evaluation of all available solutions (including all participating single and composite services). OSPG is designed to take into account user preferences, which supports optimality and robustness of the output plan. The implementation of OSPG will be con�gured and tested via division of search criteria in di�erent modes thereby locating the best plan for the user. The services composition and discovery-based model is evaluated via considering a range of criteria, such as scope, correctness, scalability and versatility metrics

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 405)

This bibliography lists 225 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Sep. 1995. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance