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The \$1000 Ian Snook Prize for 2020 will be awarded to the author(s) of themost interesting paper exploring a pair of relatively simple, but fractal,models of nonequilibrium systems, a dissipative time-reversible Baker Map andan equivalent stochastic random walk. The two-dimensional deterministic,time-reversible, chaotic, fractal, and dissipative Baker map is equivalent tothe stochastic one-dimensional random walk model for which three distinctestimates for the information dimension, $\{ \ 0.7897,\ 0.741_5, \ 0.7337 \ \}$have all been put forward. So far there is no cogent explanation for thedifferences among them. We describe the three routes to the informationdimension, $D_I$: [ 1 ] iterated Cantor-like mappings, [ 2 ] mesh-basedanalyses of single-point iterations, and [ 3 ] the Kaplan-Yorke Lyapunovdimension, thought by many to be exact for these models. We encouragecolleagues to address this Prize Problem by suggesting, testing, and analyzingmechanisms underlying these differing results.

2020 Ian Snook Prize Problem : Three Routes to the Information  Dimensions for a One-Dimensional Stochastic Random Walk and for an Equivalent  Prototypical Two-Dimensional Baker Map