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Features and fluents (vol. 1): the representation of knowledge about dynamical systemsJune 1995
Publisher:
  • Oxford University Press, Inc.
  • 198 Madison Ave. New York, NY
  • United States
ISBN:978-0-19-853845-5
Published:01 June 1995
Pages:
328
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Cited By

  1. Haslum P, Ivankovic F, Ramírez M, Gordon D, Thiébaux S, Shivashankar V and Nau D (2019). Extending classical planning with state constraints, Journal of Artificial Intelligence Research, 62:1, (373-431), Online publication date: 1-May-2018.
  2. Arenas M, Baier J, Navarro J and Sardina S Incomplete causal laws in the situation calculus using free fluents Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, (907-914)
  3. ACM
    Mitsch S, Platzer A, Retschitzegger W and Schwinger W (2015). Logic-Based Modeling Approaches for Qualitative and Hybrid Reasoning in Dynamic Spatial Systems, ACM Computing Surveys, 48:1, (1-40), Online publication date: 29-Sep-2015.
  4. Thielscher M Simulation of Action Theories and an Application to General Game-Playing Robots Essays Dedicated to Gerhard Brewka on the Occasion of His 60th Birthday on Advances in Knowledge Representation, Logic Programming, and Abstract Argumentation - Volume 9060, (33-46)
  5. Nissan E, Asaro C, Dragoni A, Farook D and Shimony S A Quarter of Century in Artificial Intelligence and Law Part II of Essays Dedicated to Yaacov Choueka on Language, Culture, Computation. Computing of the Humanities, Law, and Narratives - Volume 8002, (452-695)
  6. Ivankovic F, Haslum P, Thiébaux S, Shivashankar V and Nau D Optimal planning with global numerical state constraints Proceedings of the Twenty-Fourth International Conferenc on International Conference on Automated Planning and Scheduling, (145-153)
  7. Erdem E and Patoglu V Applications of action languages in cognitive robotics Correct Reasoning, (229-246)
  8. Doherty P, Kvarnström J and Szałas A Temporal composite actions with constraints Proceedings of the Thirteenth International Conference on Principles of Knowledge Representation and Reasoning, (478-488)
  9. Alferes J, Eckert M and May W Evolution and reactivity in the semantic web Semantic techniques for the web, (161-200)
  10. Magnusson M and Doherty P Temporal Action Logic for Question Answering in an Adventure Game Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference, (236-247)
  11. Bell J (2007). Natural events, Journal of Artificial Intelligence Research, 30:1, (361-412), Online publication date: 1-Sep-2007.
  12. Magnusson M Natural language understanding using temporal action logic Proceedings of the Workshop KRAQ'06 on Knowledge and Reasoning for Language Processing, (28-35)
  13. Sohnius R, Ermolayev V, Jentzsch E, Keberle N, Matzke W and Samoylov V Managing Concurrent Engineering Design Processes and Associated Knowledge Proceedings of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering, (198-205)
  14. Morgenstern L (2006). Book reviews, Artificial Intelligence, 170:18, (1239-1250), Online publication date: 1-Dec-2006.
  15. ACM
    Dix J, Kraus S and Subrahmanian V (2006). Heterogeneous temporal probabilistic agents, ACM Transactions on Computational Logic (TOCL), 7:1, (151-198), Online publication date: 1-Jan-2006.
  16. Mueller E (2006). Event calculus and temporal action logics compared, Artificial Intelligence, 170:11, (1017-1029), Online publication date: 1-Aug-2006.
  17. Lakemeyer G and Levesque H Semantics for a useful fragment of the situation calculus Proceedings of the 19th international joint conference on Artificial intelligence, (490-496)
  18. Alferes J and May W Evolution and reactivity for the web Proceedings of the First international conference on Reasoning Web, (134-172)
  19. Simon L, Mallya A and Gupta G Design and Implementation of A Proceedings of the 15th international conference on Logic Based Program Synthesis and Transformation, (44-60)
  20. Baldoni M, Baroglio C and Patti V (2019). Web-Based Adaptive Tutoring, Artificial Intelligence Review, 22:1, (3-39), Online publication date: 1-Sep-2004.
  21. Gustafsson J and Kvarnström J (2004). Elaboration tolerance through object-orientation, Artificial Intelligence, 153:1-2, (239-285), Online publication date: 1-Mar-2004.
  22. Davis E and Morgenstern L (2004). Introduction, Artificial Intelligence, 153:1-2, (1-12), Online publication date: 1-Mar-2004.
  23. Foo N and Peppas P Systems theory Proceedings of the 13th international conference on AI, Simulation, and Planning in High Autonomy Systems, (14-23)
  24. ACM
    Giannakopoulou D and Magee J Fluent model checking for event-based systems Proceedings of the 9th European software engineering conference held jointly with 11th ACM SIGSOFT international symposium on Foundations of software engineering, (257-266)
  25. ACM
    Giannakopoulou D and Magee J (2003). Fluent model checking for event-based systems, ACM SIGSOFT Software Engineering Notes, 28:5, (257-266), Online publication date: 1-Sep-2003.
  26. ACM
    Dix J, Kraus S and Subrahmanian V Agents dealing with time and uncertainty Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2, (912-919)
  27. Gabaldon A Non-Markovian control in the situation calculus Eighteenth national conference on Artificial intelligence, (519-524)
  28. Geffner H Perspectives on artificial intelligence planning Eighteenth national conference on Artificial intelligence, (1013-1023)
  29. Hunter A (2002). Merging structured text using temporal knowledge, Data & Knowledge Engineering, 41:1, (29-66), Online publication date: 1-Apr-2002.
  30. Thielscher M (2019). The Qualification Problem, Artificial Intelligence, 131:1-2, (1-37), Online publication date: 1-Sep-2001.
  31. Bonet B and Geffner H (2019). Planning and Control in Artificial Intelligence, Applied Intelligence, 14:3, (237-252), Online publication date: 9-May-2001.
  32. Kvarnström J and Doherty P (2019). TALplanner, Annals of Mathematics and Artificial Intelligence, 30:1-4, (119-169), Online publication date: 23-Mar-2001.
  33. ACM
    Menzel C and Grüninger M A formal foundation for process modeling Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001, (256-269)
  34. Meyer J Dynamic logic for reasoning about actions and agents Logic-based artificial intelligence, (281-311)
  35. Hölldobler S and Kuske D The boundary between decidable and undecidable fragments of the fluent calculus Proceedings of the 7th international conference on Logic for programming and automated reasoning, (436-450)
  36. Geffner H Functional strips Logic-based artificial intelligence, (187-209)
  37. Ternovskaia E Automata theory for reasoning about actions Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1, (153-158)
  38. Shanahan M The event calculus explained Artificial intelligence today, (409-430)
  39. Bertossi L, Arenas M and Ferretti C (2019). SCDBR, Journal of Intelligent Information Systems, 10:3, (253-280), Online publication date: 1-Jun-1998.
Contributors
  • Linköping University

Recommendations

Claudio Delrieux

The knowledge representation and reasoning (KR&R) problem about actions and change is discussed. The book's primary purpose is to provide novel research results on the topic. There are a number of logics for reasoning about actions and change. The purpose of this book is to provide a framework in which existing and new logics can be characterized. More than a mere assembly of test examples to check out several approaches that have been proposed, the book has a more ambitious goal: to assess various reasoning systems. Chapter 1, “Inert and Inhabited Dynamical Systems,” presents a general description of the subject, with its ontological assumptions. The structure of an inhabited dynamical system (IDS) is defined as one or more agents that interact with a reality. An agent, in turn, can be viewed as a material vehicle and an ego or knowledge-level description. A game is a set of moves, that is, actions that the agents perform on reality. A scenario for an IDS is a set of games. The definitions above allow a recasting of some benchmark problems in KR&R (the Yale shooting problem, for instance) in a common setting. This is introduced in chapter 2, “Inference Operations on Scenario Descriptions.” A point presented in this chapter is that logics for reasoning in world descriptions are essentially logics with implicit epistemological assumptions. The assumptions are introduced via designators. The next chapter focuses on the underlying semantics of IDS worlds, basically a partial (transition-state) model semantics or a functional (trajectory) semantics. The range of chronicles in which the set of selected models according to the entailment relation coincides with the set of intended models is an assessment for the entailment relation. Now the author can introduce an elementary feature logic, with its grammar, domains, syntax, and semantics. This is a first step toward the logic for expressing statements about scenario descriptions. Metalogical concepts and notations are also introduced. In chapter 5, “Lexical-domain Object-feature Logic,” the elementary logic of the preceding chapter is generalized to allow an object domain to be associated with a lexical type in the language. Members of the new domain may appear both in formulas and in the interpretations. Syntax and semantics are extended accordingly. This allows the introduction of denotations, that is, feature expressions with fully evaluated arguments. A reasoned example is presented. The next chapter introduces a discrete-time temporal feature logic. A general definition of a discrete-time structure is introduced. The syntax and semantics of the temporal feature logic use timepoints in the temporal structure as one of its sorts. With this formal apparatus, in chapter 7 some classic examples are recast as chronicle completion problems. A classification of chronicle completion problems is provided in chapter 7, and in chapter 8 the intended models for chronicles are discussed. Now the author is ready to present some of the main results of his work. In chapter 9, the general entailment problem is considered, and some methods applicable within the formal framework of the book are presented. These are based on model preference notions, that is, model selection or minimization of change. The notion of range of applicability for entailment methods is defined. Some possible improvements are discussed. In the next chapter, the knowledge representation features of the formalization are enhanced with duration constraints. The author avoids equidurationality using a preference method of chronological assignment of valuations. The final chapters discuss some other representational and formal issues, such as the representation and entailment of composite actions, and soundness considerations. The layout and typesetting of the book are adequate, but the notation tends to be quite heavy (the notation index is nine pages long). A summary is provided at the end of each chapter. Those working in nonmonotonic reasoning, planning, temporal logic, reasoning about actions and change, and related areas will find this book worth reading.

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