Figure 1.

Markov chain ruling the presented action sequences. Rows depict the first objects of a transition (t - 1), e.g., the board (first row) was always (p = 1.0) followed by a cube (third column), whereas the cube (third row) could be followed by a washer (p = 0.25), a short screw (p = 0.50), or a screw nut (p = 0.25). Conditional surprisal of an action step depended on its probability given the preceding action step only. An example is highlighted in the figure: cells surrounded by dotted lines determine the surprisal assigned to the washer after a screw nut (orange) or a cube (blue). In contrast, an action step's conditional entropy depended on its own probability and the probability weights of alternative action steps. For instance, cells surrounded by dashed lines determine the conditional entropy assigned to the washer after the screw nut (orange) or cube (blue).