doi:10.1017/S0269888920000235

Agmon , N., Urieli , D. & Stone , P.2011. Multiagent patrol generalized to complex environmental conditions. In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI 2011).

Almeida , A., Ramalho , G., Santana , H., Tedesco , P., Menezes , T., Corruble , V. & Chevaleyre , Y.2004. Recent advances on multi-agent patrolling. In Advances in Artificial Intelligence – SBIA 2004, Bazzan , A. L. C. & Labidi , S. (eds). Springer Berlin Heidelberg, 474–483. ISBN: 978-3-540-28645-5.

Baker , J. E.1985. Adaptive selection methods for genetic algorithms. In Proceedings of an International Conference on Genetic Algorithms and Their applications, Hillsdale, New Jersey, 101–111.

Berman , S., Halasz , A., Kumar , V. & Pratt , S.2007. Bio-inspired group behaviors for the deployment of a swarm of robots to multiple destinations. In Proceedings 2007 IEEE International Conference on Robotics and Automation, 2318–2323.

Campbell , A. & Wu , A. S.2011. Multi-agent role allocation: Issues, approaches, and multiple perspectives. Autonomous Agents and Multi-Agent Systems22(2), 317–355.

Campos , M., Bonabeau , E., Theraulaz , G. & Deneubourg , J.-L.2000. Dynamic scheduling and division of labor in social insects. Adaptive Behavior8(2), 83–95.

Chu , H. N., Glad , A., Simonin , O., Sempe , F., Drogoul , A. & Charpillet , F.2007. Swarm approaches for the patrolling problem, information propagation vs. pheromone evaporation. In 19th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2007, 1, 442–449. 2007.

Cicirello , V. A. & Smith , S. F.2004. Wasp-like agents for distributed factory coordination. Autonomous Agents and Multi-Agent Systems8(3), 237–266. ISSN: 1573-7454.

De Jong , K. A.2006. Evolutionary Computation: A Unified Approach, MIT Press, Cambridge, MA, USA.

dos Santos, F. & Bazzan, A. L. 2009. An ant based algorithm for task allocation in largescale and dynamic multiagent scenarios. In Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, 73–80. ACM.

dos Santos, F. & Bazzan, A. L. 2011. Towards efficient multiagent task allocation in the robocup rescue: a biologically-inspired approach. Autonomous Agents and Multi-Agent Systems22(3), 465–486.

dos Santos, D. S. & Bazzan, A. L. 2012. Distributed clustering for group formation and task allocation in multiagent systems: a swarm intelligence approach. Applied Soft Computing12(8), 2123–2131. ISSN: 1568-4946.

Ducatelle , F., Förster , A., Di Caro , G. A. & Gambardella , L. M.2009. New task allocation methods for robotic swarms. In 9th IEEE/RAS Conference on Autonomous Robot Systems and Competitions.

Farinelli , A., Iocchi , L., Nardi , D. & Ziparo , V. A.2006. Assignment of dynamically perceived tasks by token passing in multirobot systems. Proceedings of the IEEE94(7), 1271–1288.

Ghizzioli , R., Nouyan , S., Birattari , M. & Dorigo , M.2005. An Ant-Based Algorithm for the Heterogeneous Dynamic Task Allocation Problem, Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle (IRIDIA), Technical Report TR/IRIDIA/2005-005.

Halász , A., Hsieh , M. A., Berman , S. & Kumar , V.2007. Dynamic redistribution of a swarm of robots among multiple sites. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007, 2320–2325. IEEE.

Hsieh , M. A., Halász , Á., Berman , S. & Kumar , V.2008. Biologically inspired redistribution of a swarm of robots among multiple sites. Swarm Intelligence2(2–4), 121–141.

Hsieh , M. A., Halász , Á., Cubuk , E. D., Schoenholz , S. & Martinoli , A.2009. Specialization as an optimal strategy under varying external conditions. In IEEE International Conference on Robotics and Automation, ICRA 2009, 1941–1946.

Kanakia , A., Touri , B. & Correll , N.2016. Modeling multi-robot task allocation with limited information as global game. Swarm Intelligence10(2), 147–160.

Kazakova , V. A., Wu , A. S. & Rahman , T. S.2013. Cluster energy optimizing genetic algorithm. In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, 1317–1324. ACM.

Kazakova , V. A. & Wu , A. S.2018. Specialization vs. re-specialization: Effects of hebbian learning in a dynamic environment. In Florida Artificial Intelligence Research Society Conference FLAIRS-31.

Kira , Z. & Arkin , R. C.2004. Forgetting bad behavior: memory for case-based navigation. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 4, 3145–3152.

Li , L., Martinoli , A. & Abu-Mostafa , Y. S.2002. Emergent specialization in swarm systems. In International Conference on Intelligent Data Engineering and Automated Learning, 261–266. Springer.

Liu , W., Winfield , A. F., Sa , J., Chen , J. & Dou , L.2007. Towards energy optimization: emergent task allocation in a swarm of foraging robots. Adaptive Behavior15(3), 289–305.

Ma , H., Li , J., Kumar , T. & Koenig , S.2017. Lifelong multi-agent path finding for online pickup and delivery tasks. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, International Foundation for Autonomous Agents and Multiagent Systems, 837–845.

Mavrovouniotis , M., Li , C. & Yang , S.2017. A survey of swarm intelligence for dynamic optimization: algorithms and applications. Swarm and Evolutionary Computation33, 1–17.

McIntire , M., Nunes , E. & Gini , M.2016. Iterated multi-robot auctions for precedenceconstrained task scheduling. In Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, International Foundation for Autonomous Agents and Multiagent Systems, 1078–1086.

Merkle , D. & Middendorf , M.2004. Dynamic polyethism and competition for tasks in threshold reinforcement models of social insects. Adaptive Behavior12(3–4), 251–262.

Murciano , A., del R. MillÁn , J. & Zamora , J.Specialization in multi-agent systems through learning. Biological Cybernetics76(5), 375–382. ISSN: 1432-0770.

Nitschke , G., Schut , M. & Eiben , A.2008. Emergent specialization in biologically inspired collective behavior systems. In Intelligent Complex Adaptive Systems, 215–253. IGI Global.

Nouyan , S.2002. Agent-based approach to dynamic task allocation. In International Workshop on Ant Algorithms, 28–39. Springer.

Nouyan , S., Ghizzioli , R., Birattari , M. & Dorigo , M.2005. An insect-based algorithm for the dynamic task allocation problem. KI 19(4), 25–31.

Nunes , E., McIntire , M. & Gini , M.2016. Decentralized allocation of tasks with temporal and precedence constraints to a team of robots. In IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), 197–202. IEEE.

Ono , N. & Fukumoto , K.1996. Multi-agent reinforcement learning: a modular approach. In Second International Conference on Multiagent Systems, 252–258.

Portugal , D. & Rocha , R.2011. A survey on multi-robot patrolling algorithms. In Doctoral Conference on Computing, Electrical and Industrial Systems, 139–146. Springer.

Price , R. & Tiño , P.2004. Evaluation of adaptive nature inspired task allocation against alternate decentralised multiagent strategies. In International Conference on Parallel Problem Solving from Nature, 982–990. Springer.

Ragusa , V. R., Mathias , H. D., Kazakova , V. A. & Wu , A. S.2017. Enhanced genetic path planning for autonomous flight. In Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2017, pp. 1208–1215.

Román , J. A., Rodríguez , S. & Corchado , J. M.2014. Improving intelligent systems: specialization. In International Conference on Practical Applications of Agents and Multi-Agent Systems, 378–385. Springer.

Schwarzrock , J., Zacarias , I., Bazzan , A. L., de Araujo Fernandes , R. Q., Moreira , L. H. & de Freitas , E. P.2018. Solving task allocation problem in multi unmanned aerial vehicles systems using swarm intelligence. Engineering Applications of Artificial Intelligence72, 10–20.

Stanley , K. O. & Miikkulainen , R.2002. Evolving neural networks through augmenting topologies. Evolutionary Computation10(2), 99–127.

Theraulaz , G., Bonabeau , E. & Deneubourg , J.-L.1998. Response threshold reinforcement and division of labour in insect societies. Proceedings of the Royal Society of London B265, 327–332.

van Lon , R. R. & Holvoet , T.2017. When do agents outperform centralized algorithms?Autonomous Agents and Multi-Agent Systems31(6), 1578–1609.

Villacorta , P. J., Pelta , D. A. & Lamata , M. T.2013. Forgetting as a way to avoid deception in a repeated imitation game. Autonomous Agents and Multi-Agent Systems27(3), 329–354.

Wawerla , J. & Vaughan , R. T.2010. A fast and frugal method for team-task allocation in a multi-robot transportation system. In ICRA, 1432–1437.

Wu , A. S. & Kazakova , V. A.2017. Effects of task consideration order on decentralized task allocation using time-variant response thresholds. In Florida Artificial Intelligence Research Society Conference FLAIRS-30, 466–471.

Zhang , Z., Long , K., Wang , J. & Dressler , F.2014. On swarm intelligence inspired self-organized networking: its bionic mechanisms, designing principles and optimization approaches. IEEE Communications Surveys & Tutorials16(1), 513–537.

Zheng , X. & Koenig , S.2011. Generalized reaction functions for solving complex-task allocation problems. IJCAI Proceedings-International Joint Conference on Artificial Intelligence, 22, 478.