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020 _a9783030385613
_9978-3-030-38561-3
024 7 _a10.1007/978-3-030-38561-3
_2doi
050 4 _aQA76.76.E95
050 4 _aQ387-387.5
072 7 _aUYQE
_2bicssc
072 7 _aCOM025000
_2bisacsh
072 7 _aUYQE
_2thema
082 0 4 _a006.33
_223
245 1 0 _aKnowledge Engineering Tools and Techniques for AI Planning
_h[electronic resource] /
_cedited by Mauro Vallati, Diane Kitchin.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aVIII, 277 p. 97 illus., 53 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPreface -- Part I: Knowledge Capture and Encoding -- 1. Explanation-based Learning of Action Models -- 2. Automated Domain Model Encoding tools for Planning -- 3. A Formal Knowledge Engineering Approach for Planning and Scheduling: Applications with itSIMPLE -- 4. MyPDDL: Tools for efficiently creating PDDL domains and problems -- 5. Planning.Domains: A Tool Suite for the Planning Researcher -- 6. Modelling Planning Tasks: Representation Matters -- Part II: Interaction, Visualisation, and Explanation -- 7. An Interactive Tool for Plan Generation, Inspection and Visualization -- 8. Interactive Visualization in Planning and Scheduling -- 9. Argument-based Plan Explanation -- 10. Interactive Planning-based Hypothesis Generation with LTS++ -- 11. Web Planner: A Tool to Develop, Visualize and Test Classical Planning Domains -- Part III: Case Studies and Applications -- 12. Design of Timeline-based Planning Systems for Safe Human-Robot Collaboration -- 13. Planning in a Real-world Application: An AUV Case Study -- 14. Knowledge Engineering and Planning for Social Human-Robot Interaction: A Case Study.-.
520 _aThis book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.
650 0 _aExpert systems (Computer science).
650 0 _aKnowledge management.
650 0 _aData mining.
650 1 4 _aKnowledge Based Systems.
650 2 4 _aKnowledge Management.
650 2 4 _aData Mining and Knowledge Discovery.
700 1 _aVallati, Mauro.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKitchin, Diane.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030385606
776 0 8 _iPrinted edition:
_z9783030385620
776 0 8 _iPrinted edition:
_z9783030385637
856 4 0 _uhttps://doi.org/10.1007/978-3-030-38561-3
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c175693
_d175693