The Causal Calculator (CCalc) is a system for representing commonsense knowledge about action and change. It implements a fragment of the causal logic described in the paper ”Nonmonotonic causal theories” by Enrico Giunchiglia, Joohyung Lee, Vladimir Lifschitz, Norman McCain and Hudson Turner (Artificial Intelligence, Vol. 153, 2004, pp. 49-104). The original version of CCalc was part of Norman McCain’s dissertation, Causality in commonsense reasoning about actions (University of Texas, 1997). Now the system is being maintained by Texas Action Group at Austin. The semantics of the language of CCalc is related to default logic and logic programming. Computationally, CCalc uses ideas of satisfiability planning. (A related system, Cplus2ASP from Arizona State University, processes CCalc input using answer set solvers instead of SAT solvers.)

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  1. Lee, Joohyung; Loney, Nikhil; Meng, Yunsong: Representing hybrid automata by action language modulo theories (2017)
  2. Yalciner, Ibrahim Faruk; Nouman, Ahmed; Patoglu, Volkan; Erdem, Esra: Hybrid conditional planning using answer set programming (2017)
  3. De Giacomo, Giuseppe; Lespérance, Yves; Patrizi, Fabio: Bounded situation calculus action theories (2016)
  4. Fandinno, Jorge: Deriving conclusions from non-monotonic cause-effect relations (2016)
  5. Inclezan, Daniela; Gelfond, Michael: Modular action language $\mathcalALM$ (2016)
  6. Lent, Jeremy; Thomason, Richmond H.: Action models for conditionals (2015)
  7. Skarlatidis, Anastasios; Paliouras, Georgios; Artikis, Alexander; Vouros, George A.: Probabilistic event calculus for event recognition (2015)
  8. Ji, Jianmin; Chen, Xiaoping: A weighted causal theory for acquiring and utilizing open knowledge (2014)
  9. Babb, Joseph; Lee, Joohyung: Cplus 2ASP: computing action language $\cal C$+ in answer set programming (2013)
  10. Giordano, Laura; Martelli, Alberto; Theseider Dupré, Daniele: Reasoning about actions with Temporal Answer Sets (2013)
  11. Strass, Hannes; Thielscher, Michael: A general first-order solution to the ramification problem with cycles (2013)
  12. Armando, Alessandro; Giunchiglia, Enrico; Maratea, Marco; Ponta, Serena Elisa: An action-based approach to the formal specification and automatic analysis of business processes under authorization constraints (2012)
  13. Artikis, Alexander: Dynamic specification of open agent systems (2012)
  14. Bochman, Alexander; Gabbay, Dov M.: Causal dynamic inference (2012)
  15. Cabalar, Pedro: Causal logic programming (2012)
  16. Chen, Xiaoping; Jin, Guoqiang; Yang, Fangkai: Extending action language $\mathcalC+$ by formalizing composite actions (2012)
  17. Delgrande, James: Considerations on belief revision in an action theory (2012)
  18. Eiter, Thomas; Feier, Cristina; Fink, Michael: Simulating production rules using ACTHEX (2012)
  19. Erdem, Esra; Patoglu, Volkan: Applications of action languages in cognitive robotics (2012)
  20. Ferraris, Paolo; Lee, Joohyung; Lierler, Yuliya; Lifschitz, Vladimir; Yang, Fangkai: Representing first-order causal theories by logic programs (2012)

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