Multi Target Partitioning of Sets Based on Local Information

Goebels, Andreas; Büning, Hans Kleine; Priesterjahn, Steffen; Weimer, Alexander

doi:10.1007/3-540-32391-0_133

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…The basic partitioning problem that has to be solved by the agents in each iteration is based on the (General) Online Partitioning Problem (G)OPP introduced by Goebels et al [6] and generalized in [7]. In contrast to the OPP, the GOPP allows to formally model limited agent abilities using a cost model and it introduces obstacles and special regions that influence movement, visibility, and communication of agents.…”

Section: Related Workmentioning

confidence: 99%

“…Besides one simple reactive mechanism, they also propose a communication-based approach, where agents exchange structured information by messages using a gossip-style protocol. The NEXT-TARGET STRATEGY [6] developed for the basic OPP requires the agents to know the distances to all targets. Agents simply select the nearest target, which can result in arbitrarily bad distribution values 2 .…”

Section: Related Workmentioning

confidence: 99%

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External Coordination Media in Capacity-Constrained Multiagent Systems

Kemmerich

Büning

2010

2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

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Our goal is to understand limitations of simplicity of knowledge structures and reasoning processes in Multiagent Systems. Therefore, we propose a framework that integrates external storage media and a capacity-constrained Multiagent System. Agents can store knowledge internally and on external storage media located in an environment. In some cases, agents either have to forget or to store knowledge externally due to limited internal memory. We define notions of suitable knowledge and let agents learn in the context of an iterative partitioning task problem. Using basic knowledge structures and a simple k-Nearest-Neighbor approach, we evaluate the role of limited internal memory in conjunction with strategic positioning of storage media and knowledge items. We also investigate dependencies between communication, internal memory size, frequently changing settings, and externally stored items. The results show that externally and strategically stored simple knowledge can support agents' reasoning processes. The approach is robust even in highly dynamic settings with small memory and without inter-agent communication.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

External Coordination Media in Capacity-Constrained Multiagent Systems

Kemmerich

Büning

2010

2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

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“…This algorithm is parallel in its nature. In [17], [18], Goebels et al presented a neighborhood-based strategy, a border switch strategy, and an exchange target strategy for the partitioning of large sets of agents onto multiple groups. In summary, the previous works solved the graph partitioning problem in both centralized and decentralized fashions, but in the decentralized way they are usually based on the density of node's distribution.…”

Section: B Literature Reviewmentioning

confidence: 99%

Moving targets tracking and observing in a distributed mobile sensor network

Sheng

2009

2009 American Control Conference

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Tracking and observing multiple dynamic targets is an important task in mobile sensor networks. This paper presents a novel approach to the problem of sensor splitting/merging for a mobile sensor network to track and observe multiple targets in a dynamic fashion. In this approach, a seed growing graph partition (SGGP) algorithm is proposed to solve the splitting/merging problem. Furthermore, during the process of tracking, collision avoidance and velocity matching among mobile sensors are guaranteed. To demonstrate the benefit of the SGGP algorithm in term of the total energy and time consumption when sensors split, we compare the SGGP with a random selection (RS) algorithm. Numerical experimental tests validate our theoretical results.

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“…Therefore, it would be nice if we would have a concept that can produce a very small and cheap communication structure without significantly reducing the quality of the solution. In this paper, we consider the Online Partitioning Problem (OPP) introduced in [5]. This problem, which is located in the area of Multi Agent Systems and Swarm Intelligence, deals with the association of agents with very limited and mostly local knowledge with different tasks represented as targets.…”

Section: Introductionmentioning

confidence: 99%

“…They are able to communicate with their direct neighbours and know the distance to all targets according to their position. A more detailed description of the abilities of the agents can be found in [5]. There, several basic strategies have been presented to distribute a small number of agents onto two targets, coping with the three objectives mentioned before.…”

Section: Introductionmentioning

confidence: 99%

Learning Useful Communication Structures for Groups of Agents

Goebels

IFIP International Federation for Information Processing

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Abstract. Coordination of altruistic agents to solve optimization problems can be significantly enhanced when inter-agent communication is allowed. In this paper we present an evolutionary approach to learn optimal communication structures for groups of agents. The agents learn to solve the Online Partitioning Problem, but our ideas can easily be adapted to other problem fields. With our approach we can find the optimal communication partners for each agent in a static environment. In a dynamic environment we figure out a simple relation between each position of agents in space and the optimal number of communication partners. A concept for the establishment of relevant communication connections between certain agents will be shown whereby the space the agents are located in will be divided into several regions. These regions will be described mathematically. After a learning process the algorithm assigns an appropriate number of communication partners for every agent in an -arbitrary located -group.

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Multi Target Partitioning of Sets Based on Local Information

Cited by 5 publications

References 7 publications

External Coordination Media in Capacity-Constrained Multiagent Systems

External Coordination Media in Capacity-Constrained Multiagent Systems

Moving targets tracking and observing in a distributed mobile sensor network

Learning Useful Communication Structures for Groups of Agents

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