An Integrated Toolkit for Modern Action Planning

Bützken M, Edelkamp S, Elalaoui A, et al. An Integrated Toolkit for Modern Action Planning. In: 19th Workshop on New Results in Planning, Scheduling and Design (PUK). 2005: 1-11.In this paper we introduce to the architecture and the abilities of our design and analysis workbench for modern action planning. The toolkit provides automated domain analysis tools together with PDDL learning capabilities. New optimal and suboptimal planners extend state-of-the-art technology. With the tool, domain experts assist solving hard combinatorial problems. Approximate or incremental solutions provided by the system are supervised. Intermediate results are accessible to improve domain modeling and to tune exploration in generating high quality plans, which, in turn, can be bootstrapped for domain inference

Knowledge acquisition and knowledge engineering in the ModPlan workbench

In this paper we present the architecture and the abilities of the ModPlan Workbench; an interacive knowledge acquisition and engineering tool for AI planning. It provides automated domain analysis tools together with PDDL learning capabilities. Integrated optimal and suboptimal planning technology extends state-of-the-art technology. With the tool, domain experts assist solving hard combinatorial problems. Approximate or incremental solutions provided by the system are supervised. Intermediate results are accessible to improve domain modeling and to tune exploration in generating enhanced plans, which, in turn, can be bootstrapped for domain description inference

Trail-directed Java Program Verification

This paper introduces the application of trail-based heuristics for software verification. Trail-directed program verification serves the purpose of shortening an error trail, so that it will be more comprehensible for the user. We explain the concept of two heuristics that are based on the Hamming- and FSM-distance between states of a Java program. We then utilize the Java software verifier JPF to implement and test the new heuristics and to compare them to the heuristics that are already provided by this tool

Tag der mündlichen Prüfung:

□ ausgezeichnet □ sehr gut □ gut □ genügendFür meine Eltern. 4Acknowledgements Hereby, I would like to thank my advisor Dr. Stefan Edelkamp, for his excellent guidance. Without his various original ideas, his broad theoretical and practical knowledge, his reviews and moral support, this thesis would not exist. Moreover, I thank Prof. Dr. Katharina Morik and Dr. Doris Schmedding who agreed to review my thesis. Also, I want to thank Shahid Jabbar for his support and his reviews. Further acknowledgements must go to the German Research Society (DFG) who financially supported my research through the project Directed Model Checking with Exploration Algorithms of Artificial Intelligence. Last, but not least, I would like to thank my girlfriend Frida as well as my friends and family for their moral support. 5

An Integrated Toolkit for Modern Action Planning

Abstract. In this paper we introduce to the architecture and the abilities of our design and analysis workbench for modern action planning. The toolkit provides automated domain analysis tools together with PDDL learning capabilities. New optimal and suboptimal planners extend state-of-the-art technology. With the tool, domain experts assist solving hard combinatorial problems. Approximate or incremental solutions provided by the system are supervised. Intermediate results are accessible to improve domain modeling and to tune exploration in generating high quality plans, which, in turn, can be bootstrapped for domain inference.