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Seminar: Theorien induktiven und deduktiven Denkens aus KI und Psychologie - Themen

Hintergrundliteratur

Denken und Kognitionswissenschaft

  • Beller, S., & Spada, H. (1996). Denken [Reasoning]. In G. Strube, B. Becker, C. Freksa, U. Hahn, G. Palm, & K. Opwis (Eds.), Wörterbuch der Kognitionswissenschaft, pp. 114-124, Klett-Cotta.
  • Opwis, K. (1996). Modellierung, kognitive [cognitive modeling]. In Wörterbuch der Kognitionswissenschaft, pp. 407-408, Klett-Cotta.

Inhaltseffekte

  • Neth, H., & Beller, S. (1999). How knowledge interferes with reasoning - Suppression effects by content and context. In Proc. of the 21st Annual Conference of the Cognitive Science Society, pp. 468-473, Lawrence Erlbaum. (PDF)

Inferenz, formale Systeme

  • Kerber, M., & Sieckmann, J. (1996). Inferenzverfahren. In Wörterbuch der Kognitionswissenschaft, pp. 267-275, Klett-Cotta.

Mentale Modelle

  • Johnson-Laird, P.N. (2001). Mental models and deduction. Trends In Cognitive Sciences 5(10): 434-442.

 
 

A. Inhalt und Kontext

A1. Inhaltseffekte (KogWis)

  • Byrne, R.M. (1989). Suppressing valid inferences with conditionals. Cognition 31(1), 61-83.
    (PDF)
  • Beller, S., & Spada, H. (2003). The logic of content effects in propositional reasoning: The case of conditional reasoning with a point of view. Thinking and Reasoning 9(4), 335-378.
    (PDF)
  • Neth, H., & Beller, S. (1999). How knowledge interferes with reasoning – suppression effects by content and context. In M. Hahn, & S. C. Stoness (Eds.), Proc. of the Twenty First Annual Conference of the Cognitive Science Society, pp. 468- 473, Lawrence Erlbaum.
    (PDF)

Betreuung: Gregory Kuhnmuench
Bearbeitung: Maximilian Heise
Kommentar: Eva-Maria Steinlein

B. Schließen mit Wahrscheinlichkeiten

B1. Schließen mit Wahrscheinlichkeiten und nicht-monotones Schließen (KogWis)

  • Oaksford, M., & N. Chater (2001). The probabilistic approach to human reasoning. Trends in Cognitive Sciences 5, 349-357.
    (PDF)
  • Oaksford, M., & N. Chater (2002). Commonsense reasoning, logic and human rationality. In R. Elio (Ed.), Commonsense reasoning and rationality, Oxford University Press.
  • Chater, N., & M. Oaksford (1999). Information gain vs. decision-theoretic approaches to data selection: Response to Klauer. Psychological Review 106, 223-227.

Betreuung: PD Dr. Marco Ragni
Bearbeitung: Eva-Maria Steinlein
Kommentar: Tobias Seufert

B2. Nicht-monotones Schließen beim Menschen (KogWis / Inf)

  • Fugard, A.J.B., Pfeifer, N., & Mayerhofer, B. (2011). Probabilistic theories of reasoning need pragmatics too: Modulating relevance in uncertain conditionals. Journal of Pragmatics 43, 2034–2042.
    (PDF)
  • Fugard, A.J.B., Pfeifer, N., Mayerhofer, B. & Kleiter, G.D. (2011). How people interpret conditionals: Shifts towards the conditional event. Journal of Experimental Psychology: Learning, Memory, and Cognition 37(3), 635-648.
    (PDF)
  • Pfeifer, N. & Kleiter, G.D. (2007). Nonmonotonicity and human probabilistic reasoning. Technical report.
    (PDF)

Betreuung: PD Dr. Marco Ragni
Bearbeitung: Dina Yunusova
Kommentar: Robert Grönsfeld

B3. Probabilistische Modelle für konditionales Schließen (KogWis)

  • Klauer, K.C., Beller, S., & Hütter, M. (2010). Conditional reasoning in context: A dual-source model of probabilistic inference. Journal of Experimental Psychology: Learning, Memory, and Cognition 36, 298-323.
    (PDF)

Betreuung: PD Dr. Marco Ragni
Bearbeitung: NN
Kommentar: NN

B4. Bayes’sche Netze (Inf)

  • Russel, S., & Norvig, P. (2010). Probabilistic reasoning. Kap. 14 aus Artificial Intelligence: A modern approach, Pearson, pp. 510-565.

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Martin Goth
Kommentar: Josef Huber

C. Nicht-monotones Schließen

C1. Default-Logik (Ideen und grundlegende Konzepte) (Inf)

  • Reiter, R. (1980). A logic for default reasoning. Artificial Intelligence 13 (1–2), 81–132.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Raphael Schmitt
Kommentar: Axel Lehmann

C2. Default-Logik (Varianten of Reiters Default-Logik) (Inf)

  • Delgrande, J.P., T. Schaub, & W.K. Jackson (1994). Alternative approaches to default logic. Artificial Intelligence 70(1–2), 167–237.
    (PDF)
  • Delgrande, J.P., & T. Schaub (2003). On the relation between Reiter's default logic and its (major) variants. Proc. of Symbolic and Quantitative Approaches to Reasoningwith Uncertainty.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: André Doser
Kommentar: Fabian Wenzelmann

C3. Default Reasoning (KogWis / Inf)

  • Pelletier, F.J., & R. Elio (1997). What Should Default Reasoning be, by Default?. Computational Intelligence 13: 165–187.
    (PDF)
  • Pelletier, F.J., & R. Elio (1993). Human Benchmarks on AI's Benchmark Problems. Proceedings of the 15th Congress of the Cognitive Science Society.
    (PDF)
  • Elio, R., & F. Pelletier (1996). On Reasoning with Default Rules and Exceptions. Proceedings of the 18th Annual Conference on Cognitive Science, Lawrence Erlbaum: Hillsdale, NJ, pp. 131-136.
    (PDF)

Betreuung: PD Dr. Marco Ragni
Bearbeitung: Josef Huber
Kommentar: Raphael Schmitt

C4. Kumulative Logiken (Systemvergleich) (Inf)

  • Kraus, S., D. Lehmann, & M. Magidor (1990). Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence 44, 167–207.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Axel Lehmann
Kommentar: Thorsten Engesser

C5. 3-wertige Logiken und nicht-monotones Schließen (KogWis / Inf)

  • Stenning, K., & M. van Lambalgen (2004). A little logic goes a long way: basing experiment on semantic theory in the cognitive science of conditional reasoning. Cognitive Science 28(4):481–530.
    (PDF)
  • Stenning, K., & M. van Lambalgen (2005). Semantic interpretation as reasoning in nonmonotonic logic: the real meaning of the suppression task. Cognitive Science 29(6):919–960.
    (PDF)

Betreuung: PD Dr. Marco Ragni
Bearbeitung: NN
Kommentar: NN

D. Schließen unter Unsicherheit

D1. Dempster-Shafer-Therorie (Inf)

  • Yager, R.R. (1987). On the Dempster-Shafer framework and new combination rules. Information Sciences 41(2), 93–137.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Daniel Jäckle
Kommentar: Johanna Götz

D2. Plausibilitätsmaße (Inf)

  • Friedman, N., & J.Y. Halpern (2001). Plausibility measures and default reasoning. J. of the ACM 48(4): 648-685.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Florian Geißer
Kommentar: Jan Mortensen

D3. Approximatives Schließen (Inf)

  • Zadeh, L.A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3-28.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: NN
Kommentar: NN

E. Kausales Schließen

E1. Kausales Denken und mentale Modelle (KogWis)

  • Goldvarg, E., & Johnson-Laird, P.N. (2001). Naive causality: A mental model theory of causal meaning and reasoning. Cognitive Science 25 (4), 565-610.
    (PDF)
  • Kuhnmünch, G., & Beller, S. (2005). Distinguishing between causes and enabling conditions - through mental models or linguistic cues?. Cognitive Science 29, 1077-1090.
    (PDF)

Betreuung: Gregory Kuhnmuench
Bearbeitung: Tomas Weinert
Kommentar: Stephanie Schwenke

E2. Kausale Graphen (Inf)

  • Pearl, J. (2004). Graphical models for probabilistic and causal reasoning. In A.B. Tucker (Ed.), Computer Science Handbook, Kap. 70..
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Patrick Brosi
Kommentar: Florian Geißer

E3. Kausales Schließen (Inf)

  • Kuipers, B. (1984). Commonsense Reasoning about causality: Deriving behavior from structure. Artificial Intelligence 24(1-3): 169-203.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Jan Mortensen
Kommentar: Marc Eisenbarth

F. Kohärenz und Konsistenz

F1. Konsistenz/Kohärenz: Erklärungen und Inhaltseffekte (KogWis)

  • Thagard, P. (2008). Explanatory coherence. In J. E. Adler, L. J. Rips, J. E. Adler, L. J. Rips (Eds.), Reasoning: Studies of human inference and its foundations (pp. 471-513). Cambridge University Press.
  • Ford, M., & Billington, D. (2000). Strategies in human nonmonotonic reasoning. Computational Intelligence 16(3), 446-468.

Betreuung: PD Dr. Marco Ragni
Bearbeitung: NN
Kommentar: NN

F2. Konsistenz/Kohärenz: Entscheiden (KogWis)

  • Simon, D., Snow, C.J., & Read, S.J. (2004). The Redux of Cognitive Consistency Theories: Evidence Judgments by Constraint Satisfaction. Journal Of Personality And Social Psychology 86(6), 814-837.
    (PDF)
  • Simon, D., Pham, L.B., Le, Q.A., & Holyoak, K.J. (2001). The emergence of coherence over the course of decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition 27(5), 1250-1260.
    (PDF)

Betreuung: Gregory Kuhnmuench
Bearbeitung: NN
Kommentar: NN

F3. Kohärenz und Argumentsysteme (Inf)

  • Dung, P.M. (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77: 321-357.
    (PDF)
  • Dunne, P.E., & T.J.M. Bench-Capon (2002). Coherence in finite argument systems. Artificial Intelligence 141(1-2): 187-203.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Fabian Wenzelmann
Kommentar: Martin Goth

F4. Illusory Inferences (KogWis)

  • Johnson-Laird, P.N. (2006). Mental Models, Sentential Reasoning, and Illusory Inferences. In C. Held, M. Knauff, G. Vosgerau, C. Held, M. Knauff, G. Vosgerau (Eds.), Mental models and the mind: Current developments in cognitive psychology, neuroscience, and philosophy of mind (pp. 27-51), Elsevier.
  • Legrenzi, P., Girotto, V., & Johnson-Laird, P.N. (2003). Models of consistency. Psychological Science 14(2), 131-137.
    (PDF)
  • Goldvarg, Y., & Johnson-Laird, P.N. (2000). Illusions in modal reasoning. Memory & Cognition 28(2), 282-294.
    (PDF)
  • Johnson-Laird, P.N., Legrenzi, P., Girotto, V., & Legrenzi, M.S. (2000). Illusions in reasoning about consistency. Science 288(5465), 531-532.

Betreuung: Gregory Kuhnmuench
Bearbeitung: Stephanie Schwenke
Kommentar: Maximilian Heise

G. Heuristisches Denken

G1. Heuristisches Denken (KogWis)

  • Tversky, A. & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, New Series, Vol. 185, No. 4157, pp. 1124-1131.
  • Kahneman, D. & Tversky, A. (1996). On the reality of cognitive illusions. Psychological Review 103(3), 582–591.
    (PDF)
  • Kahneman, D. (2003). Maps of bounded rationality: psychology for behavioral economics. The American Economic Review 93(5), 1449–1475.
    (PDF)
  • Gigerenzer, G., & Goldstein, D.G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review 103, 650-669.
    (PDF)

Betreuung: PD Dr. Marco Ragni
Bearbeitung: Tobias Seufert
Kommentar: Tomas Weinert

H. Denken in Analogien

H1. Induktion und analoges Denken (KogWis / Inf)

  • Holyoak, K.J., & Thagard, P. (2002). Analogical mapping by constraint satisfaction. In T. A. Polk, C. M. Seifert, T. A. Polk, C. M. Seifert (Eds.) , Cognitive modeling (pp. 849-909), MIT Press.
  • Tenenbaum, J.B., Griffiths, T.L., & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends In Cognitive Sciences 10(7), 309-318.
    (PDF)

Betreuung: PD Dr. Marco Ragni
Bearbeitung: Robert Grönsfeld
Kommentar: Tim Schulte

H2. Analoges Denken und kausale Modelle (KogWis)

  • Shafto, P., Kemp, C., Bonawitz, E., Coley, J.D., & Tenenbaum, J.B. (2008). Inductive reasoning about causally transmitted properties. Cognition 109(2), 175-192.
    (PDF)
  • Lee, H., & Holyoak, K.J. (2008). The role of causal models in analogical inference. Journal of Experimental Psychology: Learning, Memory, And Cognition 34(5), 1111-1122.
    (PDF)

Betreuung: Gregory Kuhnmuench
Bearbeitung: NN
Kommentar: NN

H3. Fallbasiertes Schließen (Inf)

  • Aamodt, A., & E. Plaza (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications 7(1): 39-52.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Marc Eisenbarth
Kommentar: Daniel Jäckle

I. Lernen und Schließen auf Erklärungen

I1. Lernen aus Beispielen (Inf)

  • Quinlan, J.R. (1986). Induction of decision trees. Machine Learning 1(1): 81-106.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Johanna Götz
Kommentar: Denis Stier

I2. Induktive logische Programmierung (Inf)

  • Muggleton, S., (1991). Inductive Logic Programming. New Generation Comput. 8(4): 295-318.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Thorsten Engesser
Kommentar: Patrick Brosi

I3. Generalisierungen mit Erklärungen (Inf)

  • Mitchell, T.M, R.M. Keller, & S.T. Kedar-Cabelli (1991). Explanation-based generalization: A unifying view. Machine Learning 1(1): 47-80.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Denis Stier
Kommentar: Dina Yunusova

I4. Abduktives Schließen (Inf)

  • Kakas, A.C., R.A. Kowalski & F. Toni (1992). Abductive Logic Programming. Journal of Logic and Computation 2(6): 719-770.
    (PDF)

Betreuung: Dr. Stefan Wölfl
Bearbeitung: Tim Schulte
Kommentar: André Doser