Using artificial evolution and selection to model insect navigation

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Using artificial evolution and selection to model insect navigation Kyran Dale, Thomas S Collett  Current Biology  Volume 11, Issue 17, Pages 1305-1316 (September 2001) DOI: 10.1016/S0960-9822(01)00418-3

Figure 1 The consistency of a wasp's approach flights to a feeder is illustrated by four approaches and landings performed by one wasp. Blobs indicate the wasp's head, and the dash indicates the compass direction of its body axis—the same convention applies to the animats in later figures. In each approach, the wasp aims at the landmark (•) before flying to the feeder (+), where it adopts a consistent heading that remains the same throughout many approaches. Consequently, the landmark always takes up the same retinal position when the wasp is at the feeder. Data from [28] Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 2 Components of the animat and a schematic of the evolutionary algorithm that generates it. (a) Motors developing forward thrust are indicated by forward-pointing arrows; motors developing sideways thrust are indicated by sideways-pointing arrows. Diamonds show sensors of compass direction with sample stimulus-response curves on the right. (b) Evolutionary algorithm: each genome of the starting population is decoded (right) to form an ANN. The ANN is then embedded in an animat, whose fitness is assessed. Splicing the genomes of two fitter members of the population generates offspring. Genetic variation is introduced by mutation, insertion, deletion, and single-point crossover Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 3 Evolved navigational strategies of wasplike animats. (a) The task and three sample trajectories. The animat is released randomly on a circle 100 du from the center of the landmark (circle) and is selected to pass as close as possible to the goal (X). The trajectory divides naturally into different phases (P1–P4). In P1, the animat fixes the left edge of the landmark with its frontal retina. P2 and P3 occur when the animat is both inside and exiting the landmark. In P4, the animat maintains a constant orientation (θ) and fixes the bottom edge of the landmark (χ) with the back of its eye. Keeping χ and θ constant at the appropriate values fixes a line between landmark and goal. (b) Plot of χ against θ for the three trajectories in (a). Each trajectory has a different symbol and is labeled N, E, or S according to the release point on the starting circle. The two spirals show values of χ and θ that will maintain a line to the goal for the two edges of the landmark. (c) χ-θ plots for two further wasplike animats show that all three animats have evolved the same basic strategies Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 4 Navigational strategies of an animat evolved in an environment with five landmarks. (a) Four trajectories from different directions. (b) χ-θ plot of one landmark edge, as shown by the dashed line in (a). During P4, data points cluster on the spiral as in Figure 3b. This plot is a simplification. In fact, several landmark edges help control P4 Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 5 Trajectories at different evolutionary stages. The three trajectories shown in (a) and (b) capture the performance of the fittest animat in the population after large increases in population fitness. (a) Animats evolved to perform the standard task (as in Figure 3). At 2000 life cycles, the animat aims at the landmark and fixes its right-hand edge. After reaching the landmark, the animat circles around it. By 10,000 life cycles, P4 has partly emerged: retinal position (χ) is fixed, but orientation (θ) is not. At 40,000 life cycles, P4 is fully established. (b) Animat evolved, as in Figure 6b, from starting positions close to the goal. In this case no beacon aiming is seen. At 2000 life cycles, the animat faces in different compass directions when it is started from north and south, and it uses a sideways-left motor to reach the vicinity of the goal. By 20,000 life cycles, trajectories from the north end close to the goal, with χ and θ under partial control. Trajectories from the south are less precise. P4 is fully established for all starting positions by 80,000 life cycles Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 6 Navigational strategies that evolved when animats with sideways motors were released at starting points that were either equidistant from the landmark and goal or were closer to the goal than to the landmark. Animats were selected in windy conditions to stop at the target. (a) A single trajectory from one animat shows the starting zone (thin gray rectangle). The χ-θ plot shows three trajectories from three different starting positions. In this evolutionary run the animats were oriented to face the landmark at the start of each trajectory. (b) Plots from another animat that was randomly oriented at the start of each trajectory. S shows the starting point of a trajectory, and X shows the goal. In both these examples, and others not shown, the animat follows a line from landmark to goal, and it exhibits the same navigational strategy in P4 as do animats evolved from more distant release points Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 7 Neural networks mediating P4 in wasplike animats that were evolved under one of three different conditions. (ai) Selected to pass close to goal. (aii) As in (ai) but also subjected to random winds. (aiii) Selected to stop at the goal. (b) The effect of wind on an animat's trajectory. Wind is indicated by gray arrowheads. (c) Vector plot of an animat displaced to different grid points. The animat was fixed at a grid point facing directly away from the landmark, and the direction in which it was heading was plotted after its rotational position had stabilized. The animat tends to head toward the line to the goal from release points over a wide area Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 8 Performance of the best antlike animat evolved in the absence of wind. (a) Two trajectories. Note the frequent change of orientation throughout the trajectory. (b) χ-θ plot. The oscillating orientation during the last phase of the trajectory is reflected in a much broader clustering of points than in Figure 3. (c) The neural network that controls the path from landmark to goal. The thick dashed line between landmark and animat is the animat's bearing when it is on the line E-X. The thinner lines give the animat's most northerly (CB1) and southerly (CB2) bearings. See the text for further description Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 9 A comparison of the performance of the best antlike and wasplike animats out of 20 evolutionary runs of each type. Animats were evolved in wind to stop at the goal. 20,000 trajectories from each animat were recorded in random wind conditions. Those segments of the paths that fell within 10 du of the goal are superimposed on the plot with a gray-level scale to show the frequency with which each pixel is visited. (a) Antlike trajectories. Few of the trajectories follow the line to the goal. The cross shows the animat's ability under favorable winds to stop at the right distance or to take the correct trajectory. (b) The performance of the wasplike animat is stable despite winds. The area in which trajectories are recorded is shown by a dashed circle in the diagram of landmark and goal Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)

Figure 10 Evolving motor architectures. (a) Starting conditions. All four pairs of motors have forward thrust. (b) Motor directions, some sample trajectories, and χ-θ plots from the three best scoring animats out of ten runs. All animats have divergent axles and so can move sideways as well as forward. All have evolved the same basic strategies of approaching the landmark and fixing χ and θ when traveling from the landmark to the goal Current Biology 2001 11, 1305-1316DOI: (10.1016/S0960-9822(01)00418-3)