Abstract
A Multi-Agent algorithm works by using at least two agents to create a synergistic effect, resulting in an emergence of new possibilities which are not programmed implicitly into the various agents. To achieve this synergistic effect the algorithm has to provide the possibility to communicate and consecutively allow cooperation between the agents. Considering the use of multi-agent algorithms in search and rescue scenarios the targeted effect of the emergence is on one hand a more effective search and rescue process or on the other hand only an optimized rescue process. This paper examines the number of agents that is needed for the Multi-Agent Flood algorithm to yield the most beneficial ratio between the used number of agents and time it takes to complete the search process. Our studies show that adding more robots may not be cost efficient for the search and rescue process. This in turn allows for a better planning and coordination of robotic search teams, as the number of needed agents can be anticipated and the possible transport logistics of robots can be optimized.
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References
Becker, M., Blatt, F., Szczerbicka, H.: A multi-agent flooding algorithm for search and rescue operations in unknown terrain. In: Klusch, M., Thimm, M., Paprzycki, M. (eds.) MATES 2013. LNCS, vol. 8076, pp. 19–28. Springer, Heidelberg (2013)
Becker, M., Blatt, F., Szczerbicka, H.: A concept of layered robust communication between robots in multi-agent search & rescue scenarios. In: IEEE/ACM 18th International Symposium on Distributed Simulation and Real Time Applications (DS-RT), pp. 175–180. IEEE (2014)
Birk, A., Pathak, K., Schwertfeger, S., Chonnaparamutt, W.: The IUB rugbot: an intelligent, rugged mobile robot for search and rescue operations. In: IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR). IEEE Press (2006)
Blatt, F., Becker, M., Szczerbicka, H.: Optimizing the exploration efficiency of autonomous search and rescue agents using a concept of layered robust communication. In: IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA). pp. 1–6. IEEE (2015)
De Hoog, J., Cameron, S., Visser, A.: Selection of rendezvous points for multi-robot exploration in dynamic environments. In: International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) (2010)
Ferranti, E., Trigoni, N., Levene, M.: Brick & Mortar: an on-line multi-agent exploration algorithm. In: IEEE International Conference on Robotics and Automation, pp. 761–767. IEEE (2007)
Ferranti, E., Trigoni, N., Levene, M.: Rapid exploration of unknown areas through dynamic deployment of mobile and stationary sensor nodes. Auton. Agent. Multi-Agent Syst. 19(2), 210–243 (2009)
Hoffman, R.R., Woods, D.D.: Beyond Simon’s slice: five fundamental trade-offs that bound the performance of macrocognitive work systems. IEEE Intell. Syst. 26(6), 67–71 (2011)
Kitano, H., Tadokoro, S.: Robocup rescue: a grand challenge for multiagent and intelligent systems. AI Mag. 22(1), 39 (2001)
Klein, G., Woods, D.D., Bradshaw, J.M., Hoffman, R.R., Feltovich, P.J.: Ten challenges for making automation a “team player” in joint human-agent activity. IEEE Intell. Syst. 19(6), 91–95 (2004)
Murphy, R.R., Tadokoro, S., Nardi, D., Jacoff, A., Fiorini, P., Choset, H., Erkmen, A.M.: Search and rescue robotics. In: Siciliano, B., Khatib, O. (eds.) Handbook of Robotics, pp. 1151–1173. Springer, Heidelberg (2008)
Nagatani, K., Kiribayashi, S., Okada, Y., Tadokoro, S., Nishimura, T., Yoshida, T., Koyanagi, E., Hada, Y.: Redesign of rescue mobile robot Quince. In: IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pp. 13–18. IEEE (2011)
Rohmer, E., Yoshida, T., Ohno, K., Nagatani, K., Tadokoro, S., Koyangai, E.: Quince: a collaborative mobile robotic platform for rescue robots research and development. In: Proceedings of International Conference on Advanced Mechatronics, pp. 225–230 (2010)
Spirin, V., Cameron, S.: Rendezvous through obstacles in multi-agent exploration. In: IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pp. 1–6. IEEE (2014)
Takahashi, T., Tadokoro, S., Ohta, M., Ito, N.: Agent based approach in disaster rescue simulation-from test-bed of multiagent system to practical application. In: RoboCup 2001: Robot Soccer World Cup V, pp. 63–74 (2002)
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Blatt, F., Becker, M., Szczerbicka, H. (2016). Analysing the Cost-Efficiency of the Multi-agent Flood Algorithm in Search and Rescue Scenarios. In: Klusch, M., Unland, R., Shehory, O., Pokahr, A., Ahrndt, S. (eds) Multiagent System Technologies. MATES 2016. Lecture Notes in Computer Science(), vol 9872. Springer, Cham. https://doi.org/10.1007/978-3-319-45889-2_11
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DOI: https://doi.org/10.1007/978-3-319-45889-2_11
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