Teamwork in Animals, Robots, and Humans

Social identity and cooperation in cultural evolution

I discuss the function of social identity signaling in facilitating cooperative group formation, and how the nature of that function changes with the structure of social organization. I propose that signals of social identity facilitate assortment for successful coordination in large-scale societies, and that the multidimensional, context-dependent nature of social identity is crucial for successful coordination when individuals have to cooperate in different contexts. Furthermore, the structure of social identity is tied to the structure of society, so that as societies grow larger and more interconnected, the landscape of social identities grows more heterogeneous. This discussion bears directly on the need to articulate the dynamics of emergent, ephemeral groups as a major factor in human cultural evolution.

Evolution of Self-Organized Task Specialization in Robot Swarms

Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as "task partitioning", whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization.