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Adaptive search space pruning in complex strategic problems

Fig 6

For most of possible search parameters, search with a narrow path shutter is the dominant search strategy.

Computation reduction is computed as A) Example of a board configuration where a narrow shutter is the dominant search strategy since it shows similar probabilities for finding the winning move at substantially lower number of computations. Simulation parameters were: complexity [830], noise level [0.5], branching [5], limit number of moves [30]. B) Example of a board configuration with a trade-off between computation amount and the probability to find a winning move. For the given simulation parameters, an increase from shutter size 0 to shutter size 1 incurs a significantly higher probability to find a winning move but the number of computations increases as well. Simulation parameters were: complexity [49], noise level [0.5], branching [5], limit number of moves [30]. C) The phase space of board complexity vs. noise levels (aggregated over branching factor and search size limitations, see Methods). Each square shows the proportion of configurations in which there was a trade-off between using narrow vs. wider shutter size values: dark blue indicates configurations where the narrow shutter dominates the Pareto front (no trade-off), dark red indicates a trade-off between narrow and wider shutter values (trade-off between computation resources and accuracy). All error bars are 95% confidence intervals.

doi: https://doi.org/10.1371/journal.pcbi.1010358.g006