We compare the elementary theories of Shannon information and Kolmogorov complexity, the extent to which they have a common purpose, and wherethey are fundamentally different. We discuss and relate the basicnotions of both theories: Shannon entropy, Kolmogorov complexity, Shannon mutual informationand Kolmogorov (``algorithmic'') mutual information. We explainhow universal coding may be viewed as a middle ground betweenthe two theories. We consider Shannon's rate distortion theory, whichquantifies useful (in a certain sense) information.We use the communication of information as our guiding motif, (...) and we explain howit relates to sequential question-answer sessions. (shrink)

We argue that confusability between items should be distinguished from generalization between items. Shepard's data concern confusability, but the theories proposed by Shepard and by Tenenbaum & Griffiths concern generalization, indicating a gap between theory and data. We consider the empirical and theoretical work involved in bridging this gap. [Shepard; Tenenbaum & Griffiths].

Remembering Kolmogorov Content Type Journal Article Pages 1-3 DOI 10.1007/s11016-011-9540-6 Authors Paul M. B. Vitányi, CWI, Science Park 123, 1098 XG Amsterdam, The Netherlands Journal Metascience Online ISSN 1467-9981 Print ISSN 0815-0796.