Published online by Cambridge University Press: 01 January 2025
The proposed quantitative description of maze learning rests on the assumption that two independent processes are involved: (i) a discovery process based on trial-and-error search for the correct response, (ii) a fixation process equivalent to that observed in serial learning. The model leads to predictions that are consistent with the available experimental data. In particular, the number of trials required for fixation is independent of the number of alternatives at each choice point (and hence independent of the number of bits of information contained in each correct response).
I am grateful to W. J. Brogden, G. A. Miller, R. F. Thompson, and J. Voss for their helpful comments on an earlier draft of this paper.