Argumentatio
Argumentatio,[1] vel conclusio,[2] vel Latinitate recentiore inferentia,[3] in logica est series graduum rationalium, qui a principiis ad consecutiones logicas moventur. Quae ratio secundum traditionem in deductionem et inductionem digeritur, quae distinctio in Europa ex temporibus Aristotelis (saeculo tertio a.C.n.) aut antea nobis venit. Argumentatio est deductio quae consecutiones logicas ex principiis notis aut assumptis veris derivat, legibus inferentiae validae in logica investigatis; inductio autem est ratiocinatio ex certis principiis ad consecutionem universam motis. Tertium argumentationis genus aliquando distinguitur, insigniter a Carolo Sanders Peirce, quod abductionem ab inductione distinguit, ubi abductio est conclusio ad optimam explanationem mota.
Variae scientiae provinciae usum investigant quomodo argumentatio moveatur. Argumentatio humana (quomodo homines conclusiones concludant) intra provinciam psychologicae cognitivae per rationes ab antiquis traditas investigatur; investigatores autem intellegentiae artificiosae automataria argumentationis systemata ad conclusiones humanas imitandas excolunt. Argumentatio statistica rationes mathematicas adhibet ad conclusiones concludendas, incertitudine praesente. Quae ratiocinationem deterministicam generalem facit, incertitudine absente casu praecipuo. Argumentatio statistica datis quantitativis aut qualitativis (categoricis) utitur, quae variationibus fortuitis subiecta sint.
Nexus interni
Notae
- ↑ Etiam coniectura. D. P. Simpson, Cassell's Latin Dictionary, ed. quinta (Novi Eboraci: Wiley Publishing, 1968), 738, s.v. inference: "(1) as a logical process, argumentatio, coniectura. (2) = conclusion drawn, conclusio, coniectura."
- ↑ Etiam coniectura, deductio. John C. Traupman, Latin and English Dictionary, ed. tertia (Novi Eboraci: Bantam Books, 2007), 572, s.v. inference: "coniectura . . . deductio . . . ; (logic) conclusio."
- ↑ Vocabulum Latinum mediaevale, Webster's Ninth New Collegiate Dictionary (Springfield Massachusettae: Merriam-Webster, 1985), 619, s.v. inferential.
Bibliographia
Generalia
- Hacking, Ian (2011). An Introduction to Probability and Inductive Logic. Cambridge University Press. ISBN 978-0-521-77501-4.
- Jaynes, Edwin Thompson (2003). Probability Theory: The Logic of Science. Cambridge University Press. ISBN 978-0-521-59271-0.
- McKay, David J.C. (2003). Information Theory, Inference, and Learning Algorithms. Cambridge University Press. ISBN 978-0-521-64298-9.
- Tijms, Henk (2004). Understanding Probability. Cambridge University Press. ISBN 978-0-521-70172-3.
Conclusio inductiva
- Carnap, Rudolf; Jeffrey, Richard C., eds. (1971). Studies in Inductive Logic and Probability. 1. The University of California Press.
- Jeffrey, Richard C., ed. (1980). Studies in Inductive Logic and Probability. 2. The University of California Press. ISBN 9780520038264.
- Angluin, Dana. 1976. "An Application of the Theory of Computational Complexity to the Study of Inductive Inference." Thesis, University of California at Berkeley.
- Angluin, Dana (1980). "Inductive Inference of Formal Languages from Positive Data". Information and Control 45 (2): 117–135.
- Angluin, Dana; Smith, Carl H. (Sep 1983). "Inductive Inference: Theory and Methods". Computing Surveys 15 (3): 237–269.
- Gabbay, Dov M.; Hartmann, Stephan; Woods, John, eds. (2009). Inductive Logic. Handbook of the History of Logic. 10. Elsevier.
- Goodman, Nelson (1983). Fact, Fiction, and Forecast. Harvard University Press. ISBN 9780674290716.
Conclusio abductiva
- O'Rourke, P.; Josephson, J., eds. (1997). Automated abduction: Inference to the best explanation. AAAI Press.
- Psillos, Stathis (2009). Gabbay, Dov M.; Hartmann, Stephan; Woods, John. eds. An Explorer upon Untrodden Ground: Peirce on Abduction. Handbook of the History of Logic. 10. Elsevier. pp. 117–152.
- Oliver, Ray. 2005. "Hybrid Abductive Inductive Learning." Ph.D. thesis, University of London, Imperial College. citeseerx = 10.1.1.66.1877. PDF.
Psychologicae ratiocinationis humanae investigationes
Deductiva
- Byrne, Ruth M. J.; Johnson-Laird, P. N. (2009). ""If" and the Problems of Conditional Reasoning". Trends in Cognitive Sciences 13 (7): 282–287.
- Johnson-Laird, Philip Nicholas; Byrne, Ruth M. J. (1992). Deduction. Erlbaum
- Johnson-Laird, Philip N. (1995). Gazzaniga, M. S.. ed. Mental Models, Deductive Reasoning, and the Brain. MIT Press. pp. 999–1008
- Khemlani, Sangeet; Johnson-Laird, P. N. (2008). "Illusory Inferences about Embedded Disjunctions". Proceedings of the 30th Annual Conference of the Cognitive Science Society. Washington/DC. pp. 2128–2133.
- Knauff, Markus; Fangmeier, Thomas; Ruff, Christian C.; Johnson-Laird, P. N. (2003). "Reasoning, Models, and Images: Behavioral Measures and Cortical Activity". Journal of Cognitive Neuroscience 15 (4): 559–573.
Statistica
- McCloy, Rachel; Byrne, Ruth M. J.; Johnson-Laird, Philip N. (2009). "Understanding Cumulative Risk". The Quarterly Journal of Experimental Psychology 63 (3): 499–515.
- Johnson-Laird, Philip N. (1994). "Mental Models and Probabilistic Thinking". Cognition 50 (1–3): 189–209.
Analogica
- Burns, B. D. (1996). "Meta-Analogical Transfer: Transfer Between Episodes of Analogical Reasoning". Journal of Experimental Psychology: Learning, Memory, and Cognition 22 (4): 1032–1048.
Spatialis
- Jahn, Georg; Knauff, Markus; Johnson-Laird, P. N. (2007). "Preferred mental models in reasoning about spatial relations". Memory & Cognition 35 (8): 2075–2087.
- Knauff, Markus; Johnson-Laird, P. N. (2002). "Visual imagery can impede reasoning". Memory & Cognition 30 (3): 363–371.
- Waltz, James A.; Knowlton, Barbara J.; Holyoak, Keith J.; Boone, Kyle B.; Mishkin, Fred S.; de Menezes Santos, Marcia; Thomas, Carmen R.; Miller, Bruce L. (Mar 1999). "A System for Relational Reasoning in Human Prefrontal Cortex". Psychological Science 10 (2): 119–125.
Moralis
- Bucciarelli, Monica, Sangeet Khemlani, et P. N. Johnson-Laird. 2008. ""The Psychology of Moral Reasoning. Judgment and Decision Making 3, no. 2 (Februarius): 121–39. PDF.
Nexus externi
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Vide deductionem in Victionario. |