Authors:Alexander Jahl;Stefan Jakob;Harun Baraki;Yasin Alhamwy andKurt Geihs
Affiliation:Distributed Systems Department, University of Kassel, Wilhelmshöher Allee, Kassel, Germany
Keyword(s):Multi-Agent Systems, Cooperation and Coordination, Self Organizing Systems, Agent Models and Architectures, Task Planning and Execution.
Abstract:Large-scale dynamic environments like Industry 4.0, Smart Cities, and Search & Rescue missions require a distributed and effective management of participating autonomous units. Usually, these units and their capabilities are heterogeneous and partially unknown at design time. Thus, the management has to adapt dynamically to the current situation. Several units have to collaborate to solve common tasks, and thus have to share their knowledge. However, complex tasks typically require the splitting of a team of units into subteams that solve smaller subtasks. A common approach to tackle this problem is to employ a decentralised, self-organising system. Traditionally, such systems are modelled either agent-centric or organisation-centric. In contrast, in this paper we shift the focus to a task-centric view. Tasks are enabled to search and bind suitable execution units based on their capabilities. These units can be either single agents, teams of agents, or teams of teams. A blockchain-based allocation model supports the task-centric view and controls the distributed task assignment. We present a proof-of-concept implementation that shows the viability of our presented approach.(More)
Large-scale dynamic environments like Industry 4.0, Smart Cities, and Search & Rescue missions require a distributed and effective management of participating autonomous units. Usually, these units and their capabilities are heterogeneous and partially unknown at design time. Thus, the management has to adapt dynamically to the current situation. Several units have to collaborate to solve common tasks, and thus have to share their knowledge. However, complex tasks typically require the splitting of a team of units into subteams that solve smaller subtasks. A common approach to tackle this problem is to employ a decentralised, self-organising system. Traditionally, such systems are modelled either agent-centric or organisation-centric. In contrast, in this paper we shift the focus to a task-centric view. Tasks are enabled to search and bind suitable execution units based on their capabilities. These units can be either single agents, teams of agents, or teams of teams. A blockchain-based allocation model supports the task-centric view and controls the distributed task assignment. We present a proof-of-concept implementation that shows the viability of our presented approach.