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| Content Provider | Springer Nature Link |
|---|---|
| Author | Caticha, Ariel |
| Copyright Year | 2013 |
| Abstract | I discuss the design of the method of entropic inference as a general framework for reasoning under conditions of uncertainty. The main contribution of this discussion is to emphasize the pragmatic elements in the derivation. More specifically: (1) Probability theory is designed as the uniquely natural tool for representing states of incomplete information. (2) An epistemic notion of information is defined in terms of its relation to the Bayesian beliefs of ideally rational agents. (3) The method of updating from a prior to a posterior probability distribution is designed through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting framework includes as special cases both MaxEnt and Bayes’ rule. It therefore unifies entropic and Bayesian methods into a single general inference scheme. I find that similar pragmatic elements are an integral part of Putnam’s internal realism, of Floridi’s informational structural realism, and also of van Fraasen’s empiricist structuralism. I conclude with the conjecture that their valuable insights can be incorporated into a single coherent doctrine—an informational pragmatic realism. |
| Starting Page | 37 |
| Ending Page | 70 |
| Page Count | 34 |
| File Format | |
| ISSN | 09246495 |
| Journal | Minds and Machines |
| Volume Number | 24 |
| Issue Number | 1 |
| e-ISSN | 15728641 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2013-10-19 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Information Entropy Entropic inference Pragmatic realism Artificial Intelligence (incl. Robotics) Philosophy of Mind Game Theory, Economics, Social and Behav. Sciences Cognitive Psychology Philosophy of Science Theory of Computation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Philosophy Artificial Intelligence |
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