{"type":"ScholarlyArticle","title":"On the Conditional Logic of Simulation Models","authors":[{"name":"Duligur Ibeling","slug":"duligur-ibeling","given":"Duligur","family":"Ibeling","affiliation":"Department of Computer Science , Stanford University"},{"name":"Thomas Icard","slug":"thomas-icard","given":"Thomas","family":"Icard","affiliation":"Department of Philosophy , Stanford University"}],"abstract":"We propose analyzing conditional reasoning by appeal to a notion of intervention on a simulation program, formalizing and subsuming a number of approaches to conditional thinking in the recent AI literature. Our main results include a series of axiomatizations, allowing comparison between this framework and existing frameworks (normality-ordering models, causal structural equation models), and a complexity result establishing NP-completeness of the satisfiability problem. Perhaps surprisingly, some of the basic logical principles common to all existing approaches are invalidated in our causal simulation approach. We suggest that this additional flexibility is important in modeling some intuitive examples.","doi":"10.24963/ijcai.2018/258","url":"https://ijcai.org/proceedings/2018/258","pdf":"https://ijcai.org/proceedings/2018/0258.pdf","markdown":"https://ijcai.org/proceedings/2018/258.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/258","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":258,"pages":{"first":1868,"last":1874},"keywords":["Knowledge Representation and Reasoning: Common-Sense Reasoning","Knowledge Representation and Reasoning: Non-classical Logics for Knowledge Representation","Knowledge Representation and Reasoning: Action, Change and Causality","Knowledge Representation and Reasoning: Logics for Knowledge Representation"],"videos":[],"references":[{"position":1,"raw":"[Balkenius and Gärdenfors, 1991] Christian Balkenius and Peter Gärdenfors. Nonmonotonic inferences in neural net- works. In Proceedings of KR, 1991.","title":"Christian Balkenius and Peter Gärdenfors. Nonmonotonic inferences in neural networks","authors":"Gärdenfors Balkenius","year":"1991","venue":"Proceedings of KR","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bottou et al., 2013] Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Danis X. Charles, D. Max Chicker- ing, Elon Portugaly, Dipankar Ray, Patrice Simard, and Ed Snelson. Counterfactual reasoning and learning sys- tems: The example of computational advertising. Journal of Machine Learning Research, 14:3207-3260, 2013.","title":"Counterfactual reasoning and learning systems: The example of computational advertising","authors":"Bottou","year":"2013","venue":"Journal of Machine Learning Research","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[de Raedt and Kimmig, 2015] Luc de Raedt and Angelika Kimmig. Probabilistic (logic) programming concepts. Ma- chine Learning, 100(1):5-47, 2015.","title":"Luc de Raedt and Angelika Kimmig. Probabilistic (logic) programming concepts","authors":"De Raedt, Kimmig","year":"2015","venue":"Machine Learning","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Dean and Kanazawa, 1989] Thomas Dean and Keiji Kanazawa. A model for reasoning about persistence and causation. Computational Intelligence, 5(2):142-150, 1989.","title":"A model for reasoning about persistence and causation","authors":"Thomas Dean, Keiji Kanazawa","year":"1989","venue":"Computational Intelligence","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Delgrande, 1998] James P. Delgrande. On first-order condi- tional logics. Artificial Intelligence, 105:105-137, 1998.","title":"On first-order conditional logics","authors":"James P Delgrande","year":"1998","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Dubois and Prade, 1991] Didier Dubois and Henri Prade. Fuzzy sets in approximate reasoning, Part 1: Inference with possibility distributions. Fuzzy Sets and Systems, 40(1):182-224, 1991.","title":"Fuzzy sets in approximate reasoning, Part 1: Inference with possibility distributions","authors":"Prade Dubois, Didier Dubois, Henri Prade","year":"1991","venue":"Fuzzy Sets and Systems","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Fagin et al., 1990] Ronald Fagin, Joseph Y. Halpern, and Nimrod Megiddo. A logic for reasoning about probabil- ities. Information and Computation, 87:78-128, 1990.","title":"A logic for reasoning about probabilities","authors":"Ronald Fagin, Joseph Y Halpern, Nimrod Megiddo","year":"1990","venue":"Information and Computation","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Friedman et al., 2000] Nir Friedman, Joseph Y. Halpern, and Daphne Koller. First-order conditional logic for de- fault reasoning revisited. ACM Transactions on Computa- tional Logic, 1(2):175-207, 2000.","title":"First-order conditional logic for default reasoning revisited","authors":"Nir Friedman, Joseph Y Halpern, Daphne Koller","year":"2000","venue":"ACM Transactions on Computational Logic","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Ginsberg, 1986] Matthew L. Ginsberg. Counterfactuals. Ar- tificial Intelligence, 30:35-79, 1986.","title":"Counterfactuals","authors":"L Matthew, Ginsberg","year":"1986","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Goodman et al., 2008] Noah D. Goodman, Vikash K. Mansinghka, Daniel Roy, Keith Bonawitz, and Joshua B. Tenenbaum. Church: a language for generative models. In Proc. 24th UAI, 2008.","title":"Church: a language for generative models","authors":"Noah D Goodman, K Vikash, Daniel Mansinghka, Keith Roy, Joshua B Bonawitz, Tenenbaum","year":"2008","venue":"Proc. 24th UAI","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Goodman et al., 2015] Noah D. Goodman, Joshua B. Tenenbaum, and Tobias Gerstenberg. Concepts in a proba- bilistic language of thought. In Eric Margolis and Stephan Laurence, editors, The Conceptual Mind: New Directions in the Study of Concepts. MIT Press, 2015.","title":"Concepts in a probabilistic language of thought","authors":"Noah D Goodman, Joshua B Tenenbaum, Tobias Gerstenberg","year":"2015","venue":"The Conceptual Mind: New Directions in the Study of Concepts","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Halpern, 2000] Joseph Y. Halpern. Axiomatizing causal reasoning. Journal of AI Research, 12:317-337, 2000.","title":"Axiomatizing causal reasoning","authors":"Y Joseph, Halpern","year":"2000","venue":"Journal of AI Research","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Halpern, 2013] Joseph Y. Halpern. From causal models to counterfactual structures. Review of Symbolic Logic, 6(2):305-322, 2013.","title":"From causal models to counterfactual structures","authors":"Y Joseph, Halpern","year":"2013","venue":"Review of Symbolic Logic","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Hawthorne and Makinson, 2007] James Hawthorne and David Makinson. The quantitative/qualitative water- shed for rules of uncertain inference. Studia Logica, 86(2):247-297, 2007.","title":"The quantitative/qualitative watershed for rules of uncertain inference","authors":"Makinson Hawthorne, James Hawthorne, David Makinson","year":"2007","venue":"Studia Logica","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Ibeling, 2018] Duligur Ibeling. Causal modeling with prob- abilistic simulation models. Manuscript, 2018.","title":"Duligur Ibeling. Causal modeling with probabilistic simulation models","authors":"Ibeling","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Icard, 2017] Thomas F. Icard. From programs to causal models. In Alexandre Cremers, Thom van Gessel, and Floris Roelofsen, editors, Proceedings of the 21st Amster- dam Colloquium, pages 35-44, 2017.","title":"From programs to causal models","authors":"F Thomas, Icard","year":"2017","venue":"Proceedings of the 21st Amsterdam Colloquium","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Kocaoglu et al., 2017] Murat Kocaoglu, Christopher Sny- der, Alexandros G. Dimakis, and Sriram Vishwanath. CausalGAN: Learning causal implicit generative mod- els with adversarial training. Unpublished manuscript: https://arxiv.org/abs/1709.02023, 2017.","title":"CausalGAN: Learning causal implicit generative models with adversarial training","authors":"Murat Kocaoglu, Christopher Snyder, Alexandros G Dimakis, Sriram Vishwanath","year":null,"venue":null,"doi":null,"url":"https://arxiv.org/abs/1709.02023,2017","internal_url":null},{"position":18,"raw":"[Kraus et al., 1990] Sarit Kraus, Daniel Lehmann, and Men- achem Magidor. Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence, 44(2):167-207, 1990.","title":"Nonmonotonic reasoning, preferential models and cumulative logics","authors":"Sarit Kraus, Daniel Lehmann, Menachem Magidor","year":"1990","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Leitgeb, 2004] Hannes Leitgeb. Inference on the Low Level: An Investigation Into Deduction, Nonmonotonic Reason- ing, and the Philosophy of Cognition. Kluwer, 2004.","title":"Inference on the Low Level: An Investigation Into Deduction","authors":"Hannes Leitgeb","year":"2004","venue":"Nonmonotonic Reasoning, and the Philosophy of Cognition","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Lewis, 1973] David Lewis. Counterfactuals. Harvard Uni- versity Press, 1973.","title":"Counterfactuals","authors":"David Lewis","year":"1973","venue":null,"doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Liang and Jordan, 2008] Percy Liang and Michael I. Jordan. An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators. In 25th ICML, 2008.","title":"An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators","authors":"Percy Liang, Michael I Jordan","year":"2008","venue":"25th ICML","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Makinson, 1994] David Makinson. General patterns in non- monotonic reasoning. In D. Gabbay et al., editor, Hand- book of Logic in Artificial Intelligence and Logic Program- ming, volume III, pages 35-110. OUP, 1994.","title":"General patterns in nonmonotonic reasoning","authors":"David Makinson","year":"1994","venue":"Handbook of Logic in Artificial Intelligence and Logic Programming","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Meek and Glymour, 1994] Christopher Meek and Clark Glymour. Conditioning and intervening. The British Jour- nal for the Philosophy of Science, 45:1001-1021, 1994.","title":"Christopher Meek and Clark Glymour. Conditioning and intervening","authors":"Glymour Meek","year":"1994","venue":"The British Journal for the Philosophy of Science","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Milch et al., 2005] Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, and Andrey Kolobov. BLOG: Probabilistic models with unknown ob- jects. In Proc. 19th IJCAI, pages 1352-1359, 2005.","title":"BLOG: Probabilistic models with unknown objects","authors":"Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L Ong, Andrey Kolobov","year":"2005","venue":"Proc. 19th IJCAI","doi":null,"url":null,"internal_url":"/proceedings/2005/203"},{"position":25,"raw":"[Mirza and Osindero, 2014] Mehdi Mirza and Simon Osin- dero. Conditional generative adversarial networks. Manuscript: https://arxiv.org/abs/1709.02023, 2014.","title":"Conditional generative adversarial networks","authors":"Mehdi Mirza, Simon Osindero","year":null,"venue":null,"doi":null,"url":"https://arxiv.org/abs/1709.02023,2014","internal_url":null},{"position":26,"raw":"[Newell and Simon, 1961] Allen Newell and Herbert A. Si- mon. Computer simulation of human thinking. Science, 134(3495):2011-2017, 1961.","title":"Computer simulation of human thinking","authors":"Allen Newell, Herbert A","year":"1961","venue":"Science","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Pearl, 2009] Judea Pearl. Causality. CUP, 2009.","title":"Judea Pearl. Causality. CUP","authors":"Pearl","year":"2009","venue":null,"doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Pfeffer and Koller, 2000] Avi Pfeffer and Daphne Koller. Semantics and inference for recursive probability models. In Proc. 7th AAAI, pages 538-544, 2000.","title":"Semantics and inference for recursive probability models","authors":"Koller Pfeffer, Avi Pfeffer, Daphne Koller","year":"2000","venue":"Proc. 7th AAAI","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Poole, 2003] David Poole. First-order probabilistic infer- ence. In Proc. 18th IJCAI, 2003.","title":"First-order probabilistic inference","authors":"David Poole","year":"2003","venue":"Proc. 18th IJCAI","doi":null,"url":null,"internal_url":"/proceedings/2003/141"},{"position":30,"raw":"[Sloman, 2005] Steven A. Sloman. Causal Models: How We Think About the World and its Alternatives. OUP, 2005.","title":"Causal Models: How We Think About the World and its Alternatives","authors":"Steven A Sloman","year":"2005","venue":null,"doi":null,"url":null,"internal_url":null},{"position":31,"raw":"[Stalnaker, 1968] Robert Stalnaker. A theory of conditionals. American Philosophical Quarterly, pages 98-112, 1968.","title":"A theory of conditionals","authors":"Robert Stalnaker","year":"1968","venue":"American Philosophical Quarterly","doi":null,"url":null,"internal_url":null},{"position":32,"raw":"[Wachter et al., 2018] Sandra Wachter, Brent Mittelstadt, and Chris Russell. Counterfactual explanations with- out opening the black box: Automated decisions and the GDPR. Harvard Journal of Law and Technology, 2018.","title":"Counterfactual explanations without opening the black box: Automated decisions and the GDPR","authors":"Sandra Wachter, Brent Mittelstadt, Chris Russell","year":"2018","venue":"Harvard Journal of Law and Technology","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}