Reasoning Biases, Non‐Monotonic Logics and Belief Revision

Theoria 83 (1):29-52 (2017)

Authors
Catarina Dutilh Novaes
VU University Amsterdam
Abstract
A range of formal models of human reasoning have been proposed in a number of fields such as philosophy, logic, artificial intelligence, computer science, psychology, cognitive science, etc.: various logics, probabilistic systems, belief revision systems, neural networks, among others. Now, it seems reasonable to require that formal models of human reasoning be empirically adequate if they are to be viewed as models of the phenomena in question. How are formal models of human reasoning typically put to empirical test? One way to do so is to isolate a number of key principles of the system, and design experiments to gauge the extent to which participants do or do not follow them in reasoning tasks. Another way is to take relevant existing results and check whether a particular formal model predicts these results. The present investigation provides an illustration of the second kind of empirical testing by comparing two formal models for reasoning – namely the non-monotonic logic known as preferential logic; and a particular version of belief revision theories, screened belief revision – against the reasoning phenomenon known as belief bias in the psychology of reasoning literature: human reasoners typically seek to maintain the beliefs they already hold, and conversely to reject contradicting incoming information. The conclusion of our analysis will be that screened belief revision is more empirically adequate with respect to belief bias than preferential logic and non-monotonic logics in general, as what participants seem to be doing is above all a form of belief management on the basis of background knowledge. The upshot is thus that, while it may offer valuable insights into the nature of human reasoning, preferential logic is ultimately inadequate as a formal model of the phenomena in question.
Keywords formal models of reasoning  belief revision  belief bias  preferential logics
Categories (categorize this paper)
DOI 10.1111/theo.12108
Options
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

Our Archive


Upload a copy of this paper     Check publisher's policy     Papers currently archived: 40,131
External links

Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library

References found in this work BETA

Against Logicist Cognitive Science.Mike Oaksford & Nick Chater - 1991 - Mind and Language 6 (1):1-38.

View all 16 references / Add more references

Citations of this work BETA

No citations found.

Add more citations

Similar books and articles

Belief Revision, Non-Monotonic Reasoning, and the Ramsey Test.Charles B. Cross - 1990 - In Kyburg Henry E., Loui Ronald P. & Carlson Greg N. (eds.), Knowledge Representation and Defeasible Reasoning. Kluwer Academic Publishers. pp. 223--244.
Belief Revision.Hans Rott - 2008 - In Jonathan Eric Adler & Lance J. Rips (eds.), Reasoning: Studies of Human Inference and its Foundations. Cambridge University Press. pp. 514--534.
Irrevocable Belief Revision in Dynamic Doxastic Logic.Krister Segerberg - 1998 - Notre Dame Journal of Formal Logic 39 (3):287-306.
Belief Bias in Informal Reasoning.Valerie Thompson & Jonathan St B. T. Evans - 2012 - Thinking and Reasoning 18 (3):278 - 310.
Logic, Reasoning and Revision.Patrick Allo - 2016 - Theoria 82 (1):3-31.
The Nature of Nonmonotonic Reasoning.Charles G. Morgan - 2000 - Minds and Machines 10 (3):321-360.
A Non-Classical Logical Foundation for Naturalised Realism.Emma Ruttkamp-Bloem, Giovanni Casini & Thomas Meyer - 2015 - In P. & M. Danćak Arazim (ed.), Logica Yearbook 2014. College Publications. pp. 249-266.

Analytics

Added to PP index
2017-01-03

Total views
24 ( #336,273 of 2,237,233 )

Recent downloads (6 months)
5 ( #384,213 of 2,237,233 )

How can I increase my downloads?

Downloads

My notes

Sign in to use this feature