GOLOG: A logic programming language for dynamic domains. This paper proposes a new logic programming language called GOLOG whose interpreter automatically maintains an explicit representation of the dynamic world being modeled, on the basis of user supplied axioms about the preconditions and effects of actions and the initial state of the world. This allows programs to reason about the state of the world and consider the effects of various possible courses of action before committing to a particular behavior. The net effect is that programs may be written at a much higher level of abstraction than is usually possible. The language appears well suited for applications in high level control of robots and industrial processes, intelligent software agents, discrete event simulation, etc. It is based on a formal theory of action specified in an extended version of the situation calculus. A prototype implementation in Prolog has been developed

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  1. Aminof, Benjamin; Murano, Aniello; Rubin, Sasha; Zuleger, Florian: Verification of agent navigation in partially-known environments (2022)
  2. Baier, Jorge A.; McIlraith, Sheila A.: Knowledge-based programs as building blocks for planning (2022)
  3. De Giacomo, Giuseppe; Felli, Paolo; Logan, Brian; Patrizi, Fabio; Sardiña, Sebastian: Situation calculus for controller synthesis in manufacturing systems with first-order state representation (2022)
  4. Aranda-Corral, Gonzalo A.; Borrego-Díaz, Joaquín; Galán-Páez, Juan: A model of three-way decisions for knowledge harnessing (2020)
  5. Belle, Vaishak; Levesque, Hector J.: Regression and progression in stochastic domains (2020)
  6. D’Asaro, Fabio Aurelio; Bikakis, Antonis; Dickens, Luke; Miller, Rob: Probabilistic reasoning about epistemic action narratives (2020)
  7. De Giacomo, Giuseppe; Ternovska, Eugenia; Reiter, Ray: Non-terminating processes in the situation calculus (2020)
  8. Finzi, Alberto; Lukasiewicz, Thomas: Partially observable game-theoretic agent programming in Golog (2020)
  9. Białek, Łukasz; Dunin-Kęplicz, Barbara; Szałas, Andrzej: A paraconsistent approach to actions in informationally complex environments (2019)
  10. Delgrande, James P.; Levesque, Hector J.: An epistemic approach to nondeterminism: believing in the simplest course of events (2019)
  11. Segovia-Aguas, Javier; Jiménez, Sergio; Jonsson, Anders: Computing programs for generalized planning using a classical planner (2019)
  12. Belle, Vaishak; Levesque, Hector J.: A logical theory of localization (2016)
  13. De Giacomo, Giuseppe; Gerevini, Alfonso Emilio; Patrizi, Fabio; Saetti, Alessandro; Sardina, Sebastian: Agent planning programs (2016)
  14. De Giacomo, Giuseppe; Lespérance, Yves; Patrizi, Fabio: Bounded situation calculus action theories (2016)
  15. De Giacomo, Giuseppe; Lespérance, Yves; Patrizi, Fabio; Vassos, Stavros: Progression and verification of situation calculus agents with bounded beliefs (2016)
  16. Lin, Fangzhen: A formalization of programs in first-order logic with a discrete linear order (2016)
  17. Mo, Peiming; Li, Naiqi; Liu, Yongmei: Automatic verification of Golog programs via predicate abstraction (2016)
  18. Saribatur, Zeynep G.; Eiter, Thomas: Reactive policies with planning for action languages (2016)
  19. Andres, Benjamin; Rajaratnam, David; Sabuncu, Orkunt; Schaub, Torsten: Integrating ASP into ROS for reasoning in robots (2015)
  20. Autexier, Serge; Hutter, Dieter: SHIP -- a logic-based language and tool to program smart environments (2015)

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