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Communication, Coordination and Cooperation
Published in Weiming Shen, Douglas H. Norrie, Jean-Paul A. Barthès, Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing, 2019
Weiming Shen, Douglas H. Norrie, Jean-Paul A. Barthès
Generally, multi-agent planning of any form requires that agents share and process substantial amounts of information; hence, it is likely to require more computing and communication resources than other approaches. The centralized multi-agent planning technique shares many of the limitations of the master-slave coordination technique. Naturally, coordination in distributed multi-agent planning is much more complex than in centralized planning as there are typically no agents involved who possess a global view of the distributed system. Since coordination in some multi-agent planning techniques such as PGP is a gradual process, they may be more suitable for some domains than others.
Optimised scheduling in human–robot collaboration – a use case in the assembly of printed circuit boards
Published in International Journal of Production Research, 2018
Karin Bogner, Ulrich Pferschy, Roland Unterberger, Herwig Zeiner
Collaborative robotics can also be seen as a special case of multi-agent planning. In this field heuristics are the most commonly applied methods (Ephrati and Rosenschein 1997). A widely adopted approach is the application of local search heuristics in each agent, but recently also global heuristics (Torreno, Sapena, and Onaindia 2015) were applied to tackle the problem. As a real-world example of a multi-agent system, Rosenfeld et al. describe the successful deployment of a multi-robot system in a warehouse (Rosenfeld et al. 2016). There, the requirement is to move merchandise and equipment from one place to another in collaboration with human workers. In their work, they provide a new approach of utilising automated advising agents for assisting a human worker to better manage time and workload.