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. Belle, Vaishak; Levesque, Hector J.: A logical theory of localization (2016)
  2. De Giacomo, Giuseppe; Gerevini, Alfonso Emilio; Patrizi, Fabio; Saetti, Alessandro; Sardina, Sebastian: Agent planning programs (2016)
  3. De Giacomo, Giuseppe; Lespérance, Yves; Patrizi, Fabio: Bounded situation calculus action theories (2016)
  4. De Giacomo, Giuseppe; Lespérance, Yves; Patrizi, Fabio; Vassos, Stavros: Progression and verification of situation calculus agents with bounded beliefs (2016)
  5. Lin, Fangzhen: A formalization of programs in first-order logic with a discrete linear order (2016)
  6. Andres, Benjamin; Rajaratnam, David; Sabuncu, Orkunt; Schaub, Torsten: Integrating ASP into ROS for reasoning in robots (2015)
  7. Autexier, Serge; Hutter, Dieter: SHIP -- a logic-based language and tool to program smart environments (2015)
  8. Belle, Vaishak; Levesque, Hector J.: Robot location estimation in the situation calculus (2015)
  9. Kelly, Ryan F.; Pearce, Adrian R.: Asynchronous knowledge with hidden actions in the situation calculus (2015)
  10. Kowalski, Robert; Sadri, Fariba: Reactive computing as model generation (2015)
  11. Ghallab, Malik; Nau, Dana; Traverso, Paolo: The actor’s view of automated planning and acting: a position paper (2014)
  12. Shen, Yuping; Zhao, Xishun: Proof systems for planning under 0-approximation semantics (2014)
  13. Beck, Daniel; Lakemeyer, Gerhard: Reinforcement learning for Golog programs with first-order state-abstraction (2012)
  14. Chen, Xiaoping; Jin, Guoqiang; Yang, Fangkai: Extending action language $\mathcalC+$ by formalizing composite actions (2012)
  15. Gorbenko, Anna; Popov, Vladimir; Sheka, Andrey: Robot self-awareness: exploration of internal states (2012)
  16. Jamroga, Wojciech; Penczek, Wojciech: Specification and verification of multi-agent systems (2012)
  17. Schiffer, Stefan; Ferrein, Alexander; Lakemeyer, Gerhard: Reasoning with qualitative positional information for domestic domains in the situation calculus (2012)
  18. Alechina, Natasha; Dastani, Mehdi; Logan, Brian; Meyer, John-Jules Ch.: Reasoning about plan revision in BDI agent programs (2011)
  19. Baral, Chitta; Gelfond, Gregory: On representing actions in multi-agent domains (2011)
  20. Bienvenu, Meghyn; Fritz, Christian; Mcilraith, Sheila A.: Specifying and computing preferred plans (2011)

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