Extended Data Figure 7: IT&E works on a completely different type of robot (the robotic arm experiment).
a, The robotic arm experimental setup. b, Tested damage conditions. c, Example of behaviour performance maps (colour maps) and behaviours (overlaid arm configurations) obtained with MAP-Elites. Left: A typical behaviour–performance map produced by MAP-Elites with five example behaviours, where a behaviour is described by the angle of each of the eight joints. The colour of each point is a function of its performance (in radians squared), which is defined as having low variance in the joint angles (that is, a zigzag arm has lower performance than a straighter arm that reaches the same point). Right: Neighbouring points in the map tend to have similar behaviours, thanks to the performance function, which would penalize more jagged ways of reaching those points. That neighbours have similar behaviours justifies updating predictions about the performance of nearby behaviours after testing a single behaviour on the real (damaged) robot. d, Accuracy (in metres) versus trial number for IT&E and traditional Bayesian optimization. The experiment was conducted on the physical robot, with 15 independent replications for each of the 14 damage conditions. Accuracy is pooled from all of these 14 × 15 = 210 experiments for each algorithm. The middle lines represent medians, while the coloured areas extend to the 25th and 75th percentiles. e, Success for each damage condition. Shown is the success rate for the 15 replications for each damage condition, defined as the percentage of replicates in which the robot reaches within 5 cm of the bin centre. f, Trials required to adapt. Shown is the number of iterations required to reach within 5 cm of the bin centre. g, Accuracy after 30 physical trials for each damage condition (with the stopping criterion disabled). For f and g, the central circle is the median, the edges of the box show the 25th and 75th percentiles, the whiskers extend to the most extreme data points that are not considered outliers, and outliers are plotted individually. See experiment 1 in the Supplementary Information for methods and analysis.
