Evolution of division of labor in genetically homogenous groups

Within nature, the success of many organisms, including certain species of insects, mammals, slime molds, and bacteria, is attributed to their performance of division of labor, where individuals specialize on specific roles and cooperate to survive. The evolution of division of labor is challenging to study because of the slow pace of biological evolution and imperfect historical data. In this paper, we use digital evolution to evolve groups of clonal organisms that exhibit division of labor. We then investigate what mechanisms they use to perform division of labor (i.e., location awareness or communication) and discover that it varies according to the type of roles being performed. Lastly, we created an environment where groups of organisms needed to complete a set of tasks, but could do so as either generalists or specialists. We varied the costs of switching tasks and determined that increased costs can result in the evolution of division of labor. Moreover, a group used as a case study exhibited both division of labor and cooperative problem decomposition, where members of the group shared partial solutions to solve the full set of problems. This approach has the potential to inform predictions in biological studies, as well as achieving division of labor when using evolutionary computation to solve more complex engineering problems.

[1]  Risto Miikkulainen,et al.  COOPERATIVE COEVOLUTION OF MULTI-AGENT SYSTEMS , 2001 .

[2]  Josh C. Bongard,et al.  The Legion System: A Novel Approach to Evolving Hetrogeneity for Collective Problem Solving , 2000, EuroGP.

[3]  David B. Knoester,et al.  Cooperative network construction using digital germlines , 2008, GECCO '08.

[4]  Robert T. Pennock,et al.  The evolutionary origin of complex features , 2003, Nature.

[5]  J. Korb,et al.  Ecology of Social Evolution , 2008 .

[6]  E. M. Eddy,et al.  The germ line and development. , 1996, Developmental genetics.

[7]  Edward O. Wilson,et al.  Caste and division of labor in leaf-cutter ants (Hymenoptera: Formicidae: Atta) , 1980, Behavioral Ecology and Sociobiology.

[8]  Charles Ofria,et al.  Ecological approaches to diversity maintenance in evolutionary algorithms , 2009, 2009 IEEE Symposium on Artificial Life.

[9]  Christoph Adami,et al.  Evolution of genetic organization in digital organisms , 1999, ArXiv.

[10]  D. Floreano,et al.  Division of labour and colony efficiency in social insects: effects of interactions between genetic architecture, colony kin structure and rate of perturbations , 2006, Proceedings of the Royal Society B: Biological Sciences.

[11]  References , 1971 .

[12]  Malcolm I. Heywood,et al.  Managing team-based problem solving with symbiotic bid-based genetic programming , 2008, GECCO '08.

[13]  David B. Knoester,et al.  Harnessing Digital Evolution , 2008, Computer.

[14]  Edward O. Wilson,et al.  Caste and division of labor in leaf-cutter ants (Hymenoptera: Formicidae: Atta) , 1983, Behavioral Ecology and Sociobiology.

[15]  Marco Dorigo,et al.  Division of labor in a group of robots inspired by ants' foraging behavior , 2006, TAAS.

[16]  D. Floreano,et al.  Evolutionary Conditions for the Emergence of Communication in Robots , 2007, Current Biology.

[17]  Dario Floreano,et al.  Genetic Team Composition and Level of Selection in the Evolution of Cooperation , 2009, IEEE Transactions on Evolutionary Computation.

[18]  John Tyler Bonner,et al.  A Theory of the Control of Differentiation in the Cellular Slime Molds , 1957, The Quarterly Review of Biology.

[19]  G. Robinson Regulation of division of labor in insect societies. , 1992, Annual review of entomology.

[20]  Charles Ofria,et al.  Avida , 2004, Artificial Life.

[21]  Anna Dornhaus,et al.  Spatial organization and division of labour in the bumblebee Bombus impatiens , 2009, Animal Behaviour.

[22]  B. Crespi The evolution of social behavior in microorganisms. , 2001, Trends in ecology & evolution.

[23]  Kenneth A. De Jong,et al.  Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents , 2000, Evolutionary Computation.

[24]  A. Dornhaus,et al.  Task Selection in Honeybees - Experiments Using Multi-Agent Simulation , 1998 .