References

1. Amina Adadi & Mohammed Berrada (2018): Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI). IEEE Access 6, pp. 52138–52160, doi:10.1109/ACCESS.2018.2870052.
2. Michael Anderson & Susan Leigh Anderson (2008): ETHEL: Toward a Principled Ethical Eldercare System. In: AI in Eldercare: New Solutions to Old Problems, Papers from the 2008 AAAI Fall Symposium, Arlington, Virginia, USA, November 7-9, 2008, AAAI Technical Report FS-08-02. AAAI, pp. 4–11. Available at http://www.aaai.org/Library/Symposia/Fall/fs08-02.php.
3. Michael Anderson & Susan Leigh Anderson (2014): GenEth: A General Ethical Dilemma Analyzer. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada.. AAAI Press, pp. 253–261, doi:10.1515/pjbr-2018-0024.
4. Michael Anderson, Susan Leigh Anderson & Chris Armen (2004): Towards machine ethics. In: AAAI-04 workshop on agent organizations: theory and practice, San Jose, CA.
5. Michael Anderson, Susan Leigh Anderson & Chris Armen (2005): MedEthEx: Toward a Medical Ethics Advisor. In: Caring Machines: AI in Eldercare, Papers from the 2005 AAAI Fall Symposium, Arlington, Virginia, USA, November 4-6, 2005., AAAI Technical Report FS-05-02. AAAI Press, pp. 9–16. Available at https://www.aaai.org/Library/Symposia/Fall/fs05-02.php.
6. Konstantine Arkoudas, Selmer Bringsjord & Paul Bello (2005): Toward ethical robots via mechanized deontic logic. In: AAAI Fall Symposium on Machine Ethics, pp. 17–23.
7. Isaac Asimov (1950): I, robot. Gnome Press.
8. Katie Atkinson & Trevor J. M. Bench-Capon (2006): Addressing Moral Problems Through Practical Reasoning. In: Deontic Logic and Artificial Normative Systems, 8th International Workshop on Deontic Logic in Computer Science, DEON 2006, Utrecht, The Netherlands, July 12-14, 2006, Proceedings, Lecture Notes in Computer Science 4048. Springer, pp. 8–23, doi:10.1007/11786849_4.
9. Tom L Beauchamp & James F Childless (1991): Principles of Biomedical Ethics. International Clinical Psychopharmacology 6(2), pp. 129–130, doi:10.1001/jama.1984.03340360075041.
10. Helen Beebee, Christopher Hitchcock & Peter Menzies (2009): The Oxford handbook of causation. Oxford University Press, doi:10.1093/oxfordhb/9780199279739.001.0001.
11. Fiona Berreby, Gauvain Bourgne & Jean-Gabriel Ganascia (2017): A Declarative Modular Framework for Representing and Applying Ethical Principles. In: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2017, São Paulo, Brazil, May 8-12, 2017. ACM, pp. 96–104. Available at http://dl.acm.org/citation.cfm?id=3091145.
12. Rastislav Bodík & Emina Torlak (2012): Synthesizing Programs with Constraint Solvers. In: Computer Aided Verification - 24th International Conference, CAV 2012, Berkeley, CA, USA, July 7-13, 2012 Proceedings, Lecture Notes in Computer Science 7358. Springer, pp. 3, doi:10.1007/978-3-642-31424-7_3.
13. Ivan Bratko & Stephen Muggleton (1995): Applications of Inductive Logic Programming. Commun. ACM 38(11), pp. 65–70, doi:10.1145/219717.219771.
14. Gerhard Brewka, Thomas Eiter & Miroslaw Truszczynski (eds.) (2016): Answer Set Programming: Special Issue. AI Magazine 37(3).
15. Selmer Bringsjord, Konstantine Arkoudas & Paul Bello (2006): Toward a General Logicist Methodology for Engineering Ethically Correct Robots. IEEE Intelligent Systems 21(4), pp. 38–44. Available at https://doi.org/10.1109/MIS.2006.82.
16. François Chollet (2019): On the Measure of Intelligence. CoRR abs/1911.01547. Available at http://arxiv.org/abs/1911.01547.
17. Nicolas Cointe, Grégory Bonnet & Olivier Boissier (2016): Ethical Judgment of Agents' Behaviors in Multi-Agent Systems. In: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, Singapore, May 9-13, 2016. ACM, pp. 1106–1114. Available at http://dl.acm.org/citation.cfm?id=2937086.
18. Vincent Conitzer, Walter Sinnott-Armstrong, Jana Schaich Borg, Yuan Deng & Max Kramer (2017): Moral Decision Making Frameworks for Artificial Intelligence. In: Satinder P. Singh & Shaul Markovitch: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA. AAAI Press, pp. 4831–4835. Available at http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14651.
19. Stefania Costantini, Giovanni De Gasperis, Abeer Dyoub & Valentina Pitoni (2018): Trustworthiness and Safety for Intelligent Ethical Logical Agents via Interval Temporal Logic and Runtime Self-Checking. In: 2018 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 26-28, 2018.. AAAI Press.
20. Andrew Cropper (2020): Forgetting to Learn Logic Programs. In: The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020. AAAI Press, pp. 3676–3683. Available at https://aaai.org/ojs/index.php/AAAI/article/view/5776.
21. Andrew Cropper, Sebastijan Dumancic & Stephen H. Muggleton (2020): Turning 30: New Ideas in Inductive Logic Programming. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020. ijcai.org, pp. 4833–4839, doi:10.24963/ijcai.2020/673.
22. Abeer Dyoub, Stefania Costantini & Giovanni De Gasperis (2018): Answer set programming and agents. Knowledge Eng. Review 33, pp. e19, doi:10.1017/S0269888918000164.
23. Abeer Dyoub, Stefania Costantini & Francesca A. Lisi (2019): Learning Answer Set Programming Rules for Ethical Machines. In: Proceedings of the Thirty Fourth Italian Conference on Computational LogicCILC, June 19-21, 2019, Trieste, Italy. CEUR-WS.org. Available at http://ceur-ws.org/Vol-2396/.
24. Abeer Dyoub, Stefania Costantini & Francesca A. Lisi (2019): Towards an ILP Application in Machine Ethics. In: Inductive Logic Programming - 29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3-5, 2019, Proceedings, Lecture Notes in Computer Science 11770. Springer, pp. 26–35, doi:10.1007/978-3-030-49210-6.
25. Jean-Gabriel Ganascia (2007): Modelling ethical rules of lying with Answer Set Programming. Ethics and information technology 9(1), pp. 39–47, doi:10.1007/s10676-006-9134-y.
26. Michael Gelfond & Vladimir Lifschitz (1988): The Stable Model Semantics for Logic Programming. In: Robert Kowalski & Kenneth Bowen: Proc. of the 5th Intl. Conf. and Symposium on Logic Programming. MIT Press, pp. 1070–1080.
27. Harry J Gensler (1996): Formal Ethics. Psychology Press.
28. Sumit Gulwani, José Hernández-Orallo, Emanuel Kitzelmann, Stephen H. Muggleton, Ute Schmid & Benjamin G. Zorn (2015): Inductive programming meets the real world. Commun. ACM 58(11), pp. 90–99, doi:10.1145/2736282.
29. R. J. Henery (1995): Classification, pp. 6–16. Ellis Horwood, USA.
30. Mireille Hildebrandt (2008): Defining Profiling: A New Type of Knowledge?. In: Mireille Hildebrandt & Serge Gutwirth: Profiling the European Citizen, Cross-Disciplinary Perspectives. Springer, pp. 17–45, doi:10.1007/978-1-4020-6914-7_2.
31. John F Horty (2001): Agency and deontic logic. Oxford University Press.
32. Albert R Jonsen & Stephen Edelston Toulmin (1988): The abuse of casuistry: A history of moral reasoning. Berkeley: Univ of California Press.
33. Nikos Katzouris, Alexander Artikis & Georgios Paliouras (2015): Incremental learning of event definitions with Inductive Logic Programming. Machine Learning 100(2-3), pp. 555–585, doi:10.1007/s10994-015-5512-1.
34. Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum & Samuel J. Gershman (2016): Building Machines That Learn and Think Like People. CoRR abs/1604.00289. Available at http://arxiv.org/abs/1604.00289.
35. Himabindu Lakkaraju, Stephen H. Bach & Jure Leskovec (2016): Interpretable Decision Sets: A Joint Framework for Description and Prediction. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 13-17, 2016. ACM, pp. 1675–1684, doi:10.1145/2939672.2939874.
36. Nada Lavrac (1999): Selected techniques for data mining in medicine. Artif. Intell. Medicine 16(1), pp. 3–23, doi:10.1016/S0933-3657(98)00062-1.
37. Mark Law, Alessandra Russo & Krysia Broda (2020): The ILASP system for Inductive Learning of Answer Set Programs. CoRR abs/2005.00904. Available at https://arxiv.org/abs/2005.00904.
38. Mark Law, Alessandra Russo & Krysia Broda (2019): Logic-Based Learning of Answer Set Programs. In: Reasoning Web. Explainable Artificial Intelligence - 15th International Summer School 2019, Bolzano, Italy, September 20-24, 2019, Tutorial Lectures, Lecture Notes in Computer Science 11810. Springer, pp. 196–231, doi:10.1007/978-3-030-31423-1_6.
39. John W. Lloyd (1987): Foundations of Logic Programming, 2nd Edition. Springer.
40. Zohar Manna & Richard J. Waldinger (1980): A Deductive Approach to Program Synthesis. ACM Trans. Program. Lang. Syst. 2(1), pp. 90–121, doi:10.1145/357084.357090.
41. Gary Marcus (2018): Deep Learning: A Critical Appraisal. CoRR abs/1801.00631. Available at http://arxiv.org/abs/1801.00631.
42. David Martens, Jan Vanthienen, Wouter Verbeke & Bart Baesens (2011): Performance of classification models from a user perspective. Decis. Support Syst. 51(4), pp. 782–793, doi:10.1016/j.dss.2011.01.013.
43. Michael McGough (2018): How bad is Sacramento’s air, exactly? Google results appear at odds with reality, some say. Sacramento Bee 7.
44. J-J Ch Meyer, FPM Dignum & Roelf J Wieringa (1994): The paradoxes of deontic logic revisited: a computer science perspective. Technical Report UU-CS-1994-38.
45. Donald Michie (1988): Machine Learning in the next Five Years. In: Proceedings of the 3rd European Conference on European Working Session on Learning, EWSL’88. Pitman Publishing, Inc., USA, pp. 107–122.
46. Grégoire Montavon, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek & Klaus-Robert Müller (2017): Explaining nonlinear classification decisions with deep Taylor decomposition. Pattern Recognit. 65, pp. 211–222, doi:10.1016/j.patcog.2016.11.008.
47. Stephen Muggleton (1991): Inductive logic programming. New generation computing 8(4), pp. 295–318, doi:10.1007/BF03037089.
48. Stephen Muggleton & Luc De Raedt (1994): Inductive Logic Programming: Theory and Methods. J. Log. Program. 19/20, pp. 629–679, doi:10.1016/0743-1066(94)90035-3.
49. Stephen H. Muggleton, Ute Schmid, Christina Zeller, Alireza Tamaddoni-Nezhad & Tarek R. Besold (2018): Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP. Mach. Learn. 107(7), pp. 1119–1140, doi:10.1007/s10994-018-5707-3.
50. Heimo Müller & Andreas Holzinger (2019): Kandinsky Patterns. CoRR abs/1906.00657. Available at http://arxiv.org/abs/1906.00657.
51. Yuko Murakami (2004): Utilitarian Deontic Logic. In: Advances in Modal Logic 5, papers from the fifth conference on "Advances in Modal logic," held in Manchester, UK, 9-11 September 2004. King's College Publications, pp. 211–230.
52. Herbert James Paton (1971): The categorical imperative: A study in Kant's moral philosophy 1023. University of Pennsylvania Press.
53. Luís Moniz Pereira & António Barata Lopes (2020): Machine Ethics - From Machine Morals to the Machinery of Morality. Studies in Applied Philosophy, Epistemology and Rational Ethics 53. Springer, doi:10.1007/978-3-030-39630-5.
54. Luís Moniz Pereira & Ari Saptawijaya (2016): Programming Machine Ethics. Studies in Applied Philosophy, Epistemology and Rational Ethics 26. Springer, doi:10.1007/978-3-319-29354-7.
55. Thomas M Powers (2006): Prospects for a Kantian machine. IEEE Intelligent Systems 21(4), pp. 46–51.
56. Raymond Reiter (1980): A logic for default reasoning. Artificial intelligence 13(1-2), pp. 81–132.
57. Graeme Richards, Victor J. Rayward-Smith, PH Sönksen, S Carey & C Weng (2001): Data mining for indicators of early mortality in a database of clinical records. Artificial intelligence in medicine 22(3), pp. 215–231.
58. William David Ross (1930): The Right and the Good. Oxford University Press, Oxford, doi:10.2307/2180065.
59. Cynthia Rudin (2018): Please Stop Explaining Black Box Models for High Stakes Decisions. CoRR abs/1811.10154. Available at http://arxiv.org/abs/1811.10154.
60. Ari Saptawijaya & Luís Moniz Pereira (2016): Logic programming for modeling morality. Log. J. IGPL 24(4), pp. 510–525, doi:10.1093/jigpal/jzw025.
61. Marek Sergot (2016): Prioritised Defeasible Imperatives. Dagstuhl Seminar 16222 Engineering Moral Agents – from Human Morality to Artificial Morality. Available at https://materials.dagstuhl.de/files/16/16222/16222.MarekSergot.Slides.pdf. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.
62. Reudismam Rolim de Sousa, Gustavo Soares, Loris D'Antoni, Oleksandr Polozov, Sumit Gulwani, Rohit Gheyi, Ryo Suzuki & Bjoern Hartmann (2016): Learning Syntactic Program Transformations from Examples. CoRR abs/1608.09000. Available at http://arxiv.org/abs/1608.09000.
63. Kush R. Varshney & Homa Alemzadeh (2016): On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products. CoRR abs/1610.01256. Available at http://arxiv.org/abs/1610.01256.
64. Wendell Wallach, Colin Allen & Iva Smit (2008): Machine morality: bottom-up and top-down approaches for modelling human moral faculties. AI Soc. 22(4), pp. 565–582, doi:10.1007/s00146-007-0099-0.
65. Rebecca Wexler (2018): Life, liberty, and trade secrets: Intellectual property in the criminal justice system. Stanford Law Review 70, pp. 1343.

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