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Reasoning Strategies for Diagnostic Probability Estimates in Causal Contexts: Preference for Defeasible Deduction over Abduction

Jean-Louis Stilgenbauer, Jean Baratgin, Igor Douven
2017 International Conference on Logic Programming and Non-Monotonic Reasoning  
Our data also suggest that defeasible deduction is for individuals the most natural reasoning strategy to estimate Pr(Cause | Effect).  ...  Recently, Meder, Mayrhofer, and Waldmann [1, 2] have proposed a model of causal diagnostic reasoning that predicts an interference of the predictive probability, Pr(Effect | Cause), in estimating the diagnostic  ...  came to prefer estimating the diagnostic probability via a defeasible deduction type of reasoning when the plausibility of the rule "If cause then P(effect)" decreased.  ... 
dblp:conf/lpnmr/StilgenbauerBD17 fatcat:gngfc6mxvjfofpgvsxhxuitr4y

Major Approaches to Medical Diagnosis and their Drawbacks

Sabina MUNTEANU
2009 Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică  
The ability to reason within a dynamical environment is of a crucial importance in Artificial Intelligence.  ...  Medical diagnosis is a dynamic and very complex field which needs special attention Our quest is for a system for medical diagnosis, that could model its search space efficiently and dynamically, while  ...  Therefore, abduction represents a form of defeasible reasoning, because it depends on (possibly incomplete) knowledge available at a certain moment.  ... 
doaj:905134691bea4c138e6de57ecc626f8b fatcat:tve3gtzmineo3cpy6lpem2vysy

Index—Volumes 1–89

1997 Artificial Intelligence  
caching 1155 context-dependent importance 76 user optimization preferences 1242 context-free grammar 1118 grammar parsers 1356 grammars 155 languages 1118 context-sensitive responses 533  ...  first-order -13 11 deductive -419, 1245 default -352,444,445,450,453,455,514, 633,1138, 1182, 1222,1224,1338, 1343 defeasible -680, 913 deterministic -132 diagnostic -296,395,989, 1196, 1345  ...  112, 147,245,292,296, 303,444,453, 461,503,573,632,690,692, 1079, 1204, 1222,1339 reasoning abductive -684, 1175, 1222 logical -1124, 1217 machinery 58 1 management of evidential -328 mathematical -166,579  ... 
doi:10.1016/s0004-3702(97)80122-1 fatcat:6az7xycuifaerl7kmv7l3x6rpm

Abduction in Logic Programming [chapter]

Marc Denecker, Antonis Kakas
2002 Lecture Notes in Computer Science  
Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas  ...  This paper aims to chart out the main developments of the field over the last ten years and to take a critical view of these developments from several perspectives: logical, epistemological, computational  ...  Introduction Over the last two decades, abduction has been embraced in AI as a non-monotonic reasoning paradigm to address some of the limitations of deductive reasoning in classical logic.  ... 
doi:10.1007/3-540-45628-7_16 fatcat:purq4epxdvbpdcno5r7duilxxa

Abductive Logic Programming

A. C. KAKAS, R. A. KOWALSKI, F. TONI
1992 Journal of Logic and Computation  
Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas  ...  This paper aims to chart out the main developments of the field over the last ten years and to take a critical view of these developments from several perspectives: logical, epistemological, computational  ...  Introduction Over the last two decades, abduction has been embraced in AI as a non-monotonic reasoning paradigm to address some of the limitations of deductive reasoning in classical logic.  ... 
doi:10.1093/logcom/2.6.719 fatcat:3voi2rfiujdsrllrrgbhbf2qzq

Edited transcription of the workshop on defeasible reasoning with specificity and multiple inheritance St. Louis, April 1989

Jennie Dorosh, Ronald P. Loui
1990 ACM SIGART Bulletin  
It's probably important to look at how we do defeasible normative reasoning to get some idea about how people do defeasible reasoning in normal contexts.  ...  You'd give preference to causal relevance over statistical relevance in this situation. Pollock: Something like that seems to be happening.  ... 
doi:10.1145/122388.122389 fatcat:xqpkc37n75biheym7vydc6w5zi

Logic-Based Technologies for Intelligent Systems: State of the Art and Perspectives

Roberta Calegari, Giovanni Ciatto, Enrico Denti, Andrea Omicini
2020 Information  
Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit  ...  logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future.  ...  logic), and to reason over such knowledge.  ... 
doi:10.3390/info11030167 fatcat:e3wed54dyzabldrnml7khx37te

Epistemic Gains and Epistemic Games: Reliability and Higher Order Evidence in Medicine and Pharmacology [chapter]

Barbara Osimani
2020 Boston Studies in the Philosophy of Science  
of causation in medicine and in the soft sciences in general, and favours probabilistic approaches to scientific inference, as better equipped for defeasibility of causal inference in such domains.  ...  The former is focused on reliability as minimisation of random and systematic error, and is grounded on a categorical approach to causal assessment, whereas the latter is more focused on the high context-sensitivity  ...  I am also grateful for discussions on the topics mentioned in the paper with Rani Anjum, Jeffrey Aronson, Bengt Autzen, Seamus Bradley, Lorenzo Casini, Vincenzo Crupi, Ralph Edwards, Branden Fitelson,  ... 
doi:10.1007/978-3-030-29179-2_15 fatcat:aefaacee6zhsxbybb4ezbuqmmm

The new logic

D Gabbay
2001 Logic Journal of the IGPL  
Then if K possesses an etiology (i.e. is subject to causal forces), this precludes the question of the performing or disperforming the K-action for good or bad reasons.  ...  Against this, Donald Davidson is widely taken as having shown that far from reasons for actions precluding their having causes, reasons are causes, or more strictly, having a reason for an action is construable  ...  The sheer attractiveness of the fallacy is hard to over-estimate.  ... 
doi:10.1093/jigpal/9.2.141 fatcat:7asmpe7mbbbw3idlpvll6pvoxq

Reexamining computational support for intelligence analysis: a functional design for a future capability

James Llinas, Galina Rogova, Kevin Barry, James W. Scrofani, James Llinas, Timothy P. Hanratty
2018 Next-Generation Analyst VI  
to support beliefs Abductive reasoning to support actions Arguments are deductions based on a set of assumptions and inference rules CISpaces, Carneades Araucaria and Various others Hybrid Methods Combination  ...  of logic and probability or belief Assumption based probability/belief based argumentation.  ...  /): "Reasoning is defeasible when the corresponding argument is rationally compelling but not deductively valid.  ... 
doi:10.1117/12.2304058 fatcat:zuostyx5ynggxhhzarc6rleeny

Précis of Bayesian Rationality: The Probabilistic Approach to Human Reasoning

Mike Oaksford, Nick Chater
2009 Behavioral and Brain Sciences  
In Chapters 5 -7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood  ...  Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning.  ...  , it is abducted."  ... 
doi:10.1017/s0140525x09000284 pmid:19210833 fatcat:oi3zstx57jgcrf3ma5bcnhrj64

Popper's Severity of Test as an intuitive probabilistic model of hypothesis testing

Fenna H. Poletiek
2009 Behavioral and Brain Sciences  
In Chapters 5 -7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood  ...  Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning.  ...  , it is abducted."  ... 
doi:10.1017/s0140525x09000454 fatcat:qe5blgi54jct3jaap7p3wgc5cy

QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension [article]

Anna Rogers, Matt Gardner, Isabelle Augenstein
2021 arXiv   pre-print
We further discuss the current classifications of "reasoning types" in question answering and propose a new taxonomy.  ...  Question answering and reading comprehension have been particularly prolific in this regard, with over 80 new datasets appearing in the past two years.  ...  But SEP defines defeasible reasoning as non-deductive reasoning based on "what normally happens" [133] , which seems to presuppose the notion of probability.  ... 
arXiv:2107.12708v1 fatcat:sfwmrimlgfg4xkmmca6wspec7i

Functional Representation of Prototypes in LVQ and Relevance Learning [chapter]

Friedrich Melchert, Udo Seiffert, Michael Biehl
2016 Advances in Intelligent Systems and Computing  
The overall acceptance rate was 88% (63% for regular papers, 100% for compressed contributions and demonstration abstracts, and 91% for thesis abstracts).  ...  In addition to the regular research presentations, posters and demonstrations, we were happy to include several other elements in the program of BNAIC 2016, among which keynote presentations by Marc Cavazza  ...  Acknowledgments The research reported has been performed in the context of the project 'Designing and Understanding Forensic Bayesian Networks with Arguments and Scenarios', funded in the NWO Forensic  ... 
doi:10.1007/978-3-319-28518-4_28 fatcat:uwxvq6txmrba3ajulmblafgh2a

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey [article]

Julian Wörmann, Daniel Bogdoll, Etienne Bührle, Han Chen, Evaristus Fuh Chuo, Kostadin Cvejoski, Ludger van Elst, Tobias Gleißner, Philip Gottschall, Stefan Griesche, Christian Hellert, Christian Hesels (+34 others)
2022 arXiv   pre-print
The reasons for this are manifold and range from time and cost constraints to ethical considerations.  ...  However, the subsequent application of these models often involves scenarios that are inadequately represented in the data used for training.  ...  On top of that, there are different types of Causal Reasoning [554]: • Prediction (reasoning forward in time), • Abduction (reasoning from evidence to explanation), • Transduction (reasoning through common  ... 
arXiv:2205.04712v1 fatcat:u2bgxr2ctnfdjcdbruzrtjwot4
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