These two final and unexpected facts about body wobble explain the also-unexpected degradation of feeding behavior from generations 5 to 6. Because the fitness function rewards increased swimming speed while penalizing increased wobble, the composite score of feeding behavior drops. Keep in mind that we measured feeding behavior using the same relationships that we used in the fitness function.
Knowing what we know now, this was a mistake. We should’ve rewarded increased wobble and called it something more appropriate, like “agility.” Unfortunately, we can’t go back and change evolutionary history without completely redoing the experiments (more on why in the following pages). We calculated the fitness function every generation in order to make the next generation. But we can recalculate the feeding behavior score with increased wobble rewarded, not penalized.
When increased wobble is rewarded, we get a slightly and importantly different picture of the evolution of the composite behavior that we call feeding of Tadro3s (Figure 4.5). First, the averages of the population’s feeding behavior now undergo more change, moving both higher and lower than their means under the old fitness-based measurement scheme. Second, one of the generation-to-generation evolutionary changes is different: from generations 5 to 6, under selection, average feeding behavior now improves rather than degrades. In other words, armed with our new understanding of wobble as a positive metric of rapid maneuvers, feeding behavior actually did improve under selection!
This seems to be a most ingenious paradox. We are saying that feeding behavior declined from generations 5 to 6, but really, it improved. What? Allow me to sum up. Before the evolution of Tadro3s started, we created a fitness function that we thought was selecting for improved feeding behavior. This fitness function rewarded increases in swimming speed and penalized increases in body wobble, time to find the food, and distance from the food. In each generation, if individual Tadro3s varied enough in their feeding for the mating algorithm to create differential reproduction, then selection was both present and active as an evolutionary mechanism.
In only one case, generations 5 to 6, was selection present when average feeding behavior declined. We had measured the feeding behavior of individuals using the same four sub-behaviors and their goodness or badness as used by the fitness function. All that we changed in making the behavioral metric was to compare individuals not just in a generation but instead across all generations as well as to scale individual differences relative to the variance exhibited by all Tadro3s across all generations. Under this original fitness-based metric, we found that one apparent anomaly in feeding behavior.
FIGURE 4.5. (facing page) The evolution of feeding behavior revisited. When increases in wobble, which correspond to quick turning maneuvers, are rewarded in the new metric (black line labeled as “NEW”) rather than punished in the old (gray line labeled as “OLD”), feeding behavior has the same general pattern as before but with two important exceptions. First, the new average feeding behaviors are both higher and lower than the old averages. Second, the evolutionary transition from generations 5 to 6 is positive with the new metric, so that in all cases when selection is present, feeding behavior improves.
We ruled out random genetic change as the cause of the decrease in feeding behavior from generations 5 to 6 because the proportion of genes changed to increase structural stiffness of the tail, and structural stiffness of the tail is positively linked to swimming speed. That left us to reconsider the four sub-behaviors and their functional interactions. We discovered that in the competitive arena, increased wobble wasn’t a sign of energy inefficiency but rather agile turning maneuvers when facilitated by high swimming speed. Hence, our original idea about what constitutes good and bad feeding behavior was just plain wrong.
When we altered our after-the-fact behavioral metric, we found that feeding behavior always, in fact, improved under selection. The paradox arose because the selection was actually penalizing increased wobble when, as we know now, it should have been rewarding it. As I mentioned earlier, we would love to revise the fitness function and repeat the experiment. We’d expect that selection, when present, would be even stronger, and that the jumps might be greater. But we have one big problem with repeating the work: evolution of physically embodied Evolvabots takes loads of time and buckets of money. This is one reason you try to be as careful as possible in the design phase (see Chapter 3)!
We thought that our Evolvabot design, carefully laid out as a series of simplified representations of nature in the previous chapter, would produce a simple evolutionary pattern. We could not have been wronger.[45] We evolved two phenotypes, material stiffness, E, and length of the tail, L, that together are responsible for the structural stiffness, k, of the notochord. These traits were coded as quantitative genes housed in a diploid genome. The possessors of the tails whose phenotype was dictated by the genes competed for food. Selection, codified by our fitness function, rewarded individuals in a particular generation who behaved better in terms of increased swimming speed, decreased body wobble, decreased average distance to the food, and decreased time to find the food. For reproduction, haploid gametes were mutated and combined in a simple random mating scheme to produce the instructions for the notochords of the next generation.
Our first surprise came when we saw, after ten generations of a constant selection pressure, that the evolutionary changes in the population’s feeding behavior, tail stiffness, and gene proportions were anything but constant. Why would a constant selection pressure produce different results each generation? Part of the answer is that in each generation the other agents in the world have changed, and their different evolved behaviors alter the competitive landscape. Another part of the answer is that genetic variability contracts and expands over generational time, changing the phenotypic options available for selection to judge.
Our next surprise came when we realized that selection was only operating to produce differential reproduction in four of the ten generations. This meant that in the generations without differential reproduction the evolutionary changes in phenotype and genotype were happening because of purely random effects. In particular, mutation and genetic drift caused mutational differences and individual genomic differences to combine into relatively large effects when selection was not present.
Our final surprise came as we probed the causal connections between the structural stiffness of the notochord and feeding behavior. Feeding behavior was measured by the same sub-behaviors that we put into our fitness function—swimming speed, body wobble, average distance to the food, and time to find the food. When we correlated these sub-behaviors with structural stiffness of the notochord, we found that swimming speed and body wobble were positively and significantly correlated with structural stiffness, k, material stiffness, E, and length of the tail, L. Time and distance to the food were not. This meant that when time and distance were undergoing greater evolutionary changes than were speed and wobble, structural stiffness could be decoupled from feeding behavior. This situation was complicated by the fact that speed and wobble are positively correlated in terms of function but are negatively correlated in the fitness function. Hence, in terms of fitness, their effects would tend to cancel.
45
In case your bad-grammar detector has signaled, I should explain that I’m trying to make a self-referential joke.