Task-switching costs promote the evolution of division of labor and shifts in individuality

Abstract

From microbes to humans, the success of many organisms is achieved by dividing tasks among specialized group members. The evolution of such division of labor strategies is an important aspect of the major transitions in evolution. As such, identifying specific evolutionary pressures that give rise to group-level division of labor has become a topic of major interest among biologists. To overcome the challenges associated with studying this topic in natural systems, we use actively evolving populations of digital organisms, which provide a unique perspective on the de novo evolution of division of labor in an open-ended system. We provide experimental results that address a fundamental question regarding these selective pressures: Does the ability to improve group efficiency through the reduction of task-switching costs promote the evolution of division of labor? Our results demonstrate that as task-switching costs rise, groups increasingly evolve division of labor strategies. We analyze the mechanisms by which organisms coordinate their roles and discover strategies with striking biological parallels, including communication, spatial patterning, and task-partitioning behaviors. In many cases, under high task-switching costs, individuals cease to be able to perform tasks in isolation, instead requiring the context of other group members. The simultaneous loss of functionality at a lower level and emergence of new functionality at a higher level indicates that task-switching costs may drive both the evolution of division of labor and also the loss of lower-level autonomy, which are both key components of major transitions in evolution.

Fig. 1.

A snapshot of the tasks exported (and thus the task-specific resources used) for three colonies. Each square represents the phenotype of an organism. Squares divided into segments represent multiple tasks exported; colors denote which tasks were exported. (A) An ancestral colony in which all organisms export the NOT task exactly once. (B) A colony that evolved a generalist strategy in which all organisms export five distinct tasks a total of eight times. (C) A colony that evolved a division of labor strategy in which each organism specializes on one of seven possible tasks that it exports a total of six times. (At the instant depicted, the organisms are not exporting NOR, which other colony members export at other times).

Fig. 2.

Segments of code across a genome. (A) Portions of the ancestral genome for performing task NOT and self-replicating. (B) An evolved specialist genome from our case-study colony, with the messaging instructions highlighted in yellow. (C) The knockout version of the specialist genome described in B, where messaging instructions have been replaced with a neutral instruction (nop-X), highlighted in yellow. These knockout organisms cease to be able to perform any task at all.

Fig. 3.

Depiction of the complex system of task partitioning evolved by our case-study colony. Organisms (squares) export tasks and exchange messages (pairs of arrows) that may include the results of tasks, input values, constants, or previously received messages. Although colonies are limited to 25 organisms at a time, offspring can replace previous organisms; for this case study colony, there are 57 organisms between colony replication events. Each organism sends seven messages and receives one; only successfully received messages are depicted. Organism colors represent tasks exported and thus resources targeted by an organism; black represents organisms that did not export any task. Each message consists of two numbers and is represented by a pair of arrows whose color denotes the contents of the message. Black arrows represent messages that are not the result of a task. Inset highlights four of these organisms: the top organism exporting ORNOT (purple) sends a message containing the solutions to the OR (orange) and ORNOT (purple) tasks to a neighboring organism, which NANDs these results together to export NOT (blue) [i.e., ([A ORNOT B] NAND [A OR B] = NOT A)].

Fig. 4.

Internal circuitry used by the organisms in the case-study colony to send seven different messages (depicted as pairs of arrows). Each organism has the same internal circuitry. However, the messages that an organism receives and thus the task it exports may be different from other organisms. The first sent message contains the input values (32-bit numbers available to each organism). The second sent message contains the result of the task exported by the organism (ORNOT) and part of the contents of a message received by the organism—in this case, the result of a task exported by the other organism (OR). The remaining five sent messages contain the result of the task exported by the organism (ORNOT) and one of two constants created by the organism. One of the possible constants involves a bit shift operation (indicated by > >), which essentially makes that component of the message meaningless. Because each organism sends seven messages, but receives only one message, the contents of most messages will not be used by the group.

Fig. 5.

Internal circuitry used by organisms in the case-study colony to export logic operations varies depending on whether they have successfully received a message. (A) An organism that exports operation OR on the input values. This individual does not receive a message (grayed-out lines) and processes inputs A and B through its logic circuitry of three NAND gates. Note {[(A NAND A)] NAND [(A NAND A) NAND B]} = (A OR B). Thus, this individual performs and then exports the OR task. (B) An organism that exports the results of an ORNOT operation using the contents of a received message. This organism performs the same initial steps as the organism depicted in A. However, it successfully receives a message that overwrites the partially processed input values. It NANDs together the received values to produce the result for ORNOT, which it exports. (C) A hierarchical perspective on how multiple organisms participate via messaging in performing a more-complex logic operation. Within this figure, we depict the same two organisms as in A and B. However, we vary their shape and color to represent the internal logic operations performed, rather than the task exported. The first organism highlighted in orange is the organism in part A. This individual ORs inputs A and B together and as such is represented by an OR gate. Additionally, it passes a message with two components to the second individual: (NOT A) and (A OR B). The second organism (from B) is highlighted in red and is represented by a NAND gate, because it receives the message (represented as blue and orange lines) sent by the first organism and performs a NAND operation on the components of the message. Because of the message contents, which were created by organism A, the resulting operation is (A ORNOT B), which is exported by the organism. Note that [(NOT A) NAND (A OR B)] = (A ORNOT B). Combined, these two individuals serve as an ORNOT gate, as depicted by the large purple gate surrounding the pair of individuals.

Fig. 6.

Colony replication process. (A) Colony a (depicted in red) amasses sufficient resources to replicate. (B) A random colony from the population (b, depicted in green) is selected as the target of the replication, and the organisms within the target colony are removed. (C) The genotype of the source colony, a, is used to produce the genotype of the new colony, a', possibly with mutations. (D) One individual from the new genotype is placed into the target colony. (E) The original colony is also reset to a single organism.