Trophallaxis-inspired self-organized task exchange in heterogeneous swarms

A trophallaxis-inspired method for self-organized task exchange in a swarm of autonomous, movable, and recon-figurable agents is proposed. Two agents that meet each other can exchange tasks with each other such that each one receives tasks that fit better to its current configuration. This reduces the energy needed for reconfiguration in order to execute the received tasks. It is investigated how an increase in the speed of moving of an agent can increase its chances for getting better tasks because of a higher frequency of meetings with other agents. An interesting trade-off is studied between getting better tasks when moving faster but losing more energy for the movement. Static scenarios where the agents spent a constant fraction of their energy on movement as well as dynamic scenarios are considered and evaluated by extensive simulations.

[1]  Henrik Schiøler,et al.  Randomized Robot Trophallaxis: From concept to implementation , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[2]  R. Moritz,et al.  Trophallaxis of worker honeybees (Apis mellifera L.) of different ages , 1986, Insectes Sociaux.

[3]  Michael J. North,et al.  Experiences creating three implementations of the repast agent modeling toolkit , 2006, TOMC.

[4]  C. Melhuish,et al.  Robot Trophallaxis : Managing Energy Autonomy in Multiple Robots , 2004 .

[5]  Gerald S. Wilkinson,et al.  Food Sharing in Vampire Bats , 1990 .

[6]  Mark Witkowski,et al.  Energy Sharing for Swarms Modeled on the Common Vampire Bat , 2007, Adapt. Behav..

[7]  Masao Kubo,et al.  Collective Energy Distribution: Maintaining the Energy Balance in Distributed Autonomous Robots using Trophallaxis , 2004, DARS.

[8]  T. Schmickl,et al.  Trophallaxis among swarm-robots: A biologically inspired strategy for swarm robotics , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..

[9]  Daniel Merkle,et al.  Congestion Control in Ant Like Moving Agent Systems , 2008, BICC.

[10]  W. Farina,et al.  Food-exchange by foragers in the hive – a means of communication among honey bees? , 1996, Behavioral Ecology and Sociobiology.

[11]  Ana B Sendova-Franks,et al.  Random walk models of worker sorting in ant colonies. , 2002, Journal of theoretical biology.

[12]  Hiroshi Sato,et al.  High survivability of a large colony through a small-world relationship , 2009, Artificial Life and Robotics.

[13]  G. Buczkowski,et al.  The influence of forager number and colony size on food distribution in the odorous house ant, Tapinoma sessile , 2009, Insectes Sociaux.

[14]  Daniel Merkle,et al.  Learning from House-Hunting Ants: Collective Decision-Making in Organic Computing Systems , 2008, ANTS Conference.

[15]  Karl Crailsheim,et al.  Protein trophallaxis and the regulation of pollen foraging by honey bees (Apis mellifera L.) , 1998 .