Multi-a(ge)nt Graph Patrolling and Partitioning

Elor, Yotam; Bruckstein, Alfred M.

doi:10.1109/wi-iat.2009.125

Cited by 27 publications

(11 citation statements)

References 8 publications

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“…The resulting subgraphs are allocated to agents so that they cover the whole environment. Elor [9] proposed a segmentation method for covering a region by integrating the ant pheromone and balloon models: a region is segmented into subregions that are individually assigned to different agents. Each subregion is considered to be a balloon, the pressure of which represents the size of the subregion.…”

Section: Related Workmentioning

confidence: 99%

“…The experimental results given below are the average values for 100 trials. We compare these results with those of a conventional distributed partitioning method [9], in which agents try to divide the area into equal-size subareas by comparing the current sizes of their RAs. We call it the balloon method [9] hereafter.…”

Section: Environmentsmentioning

confidence: 99%

“…However, in these approaches, an agent's strategy affects the other's, and this interaction makes cooperation complex. The second approach is to divide the area into a number of subareas and make each agent responsible for a different subarea [2], [9]. However, performing fair division is not trivial in the latter approach; if the characteristics of the area are not uniform and the agents have different capabilities, equal-size c 2017 Information Processing Society of Japan subareas are inappropriate.…”

Section: Introductionmentioning

confidence: 99%

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Coordinated Area Partitioning Method by Autonomous Agents for Continuous Cooperative Tasks

Sea

Kato

Sugawara

2017

Journal of Information Processing

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Abstract:We describe a method for decentralized task/area partitioning for coordination in cleaning/sweeping domains with learning to identify the easy-to-dirty areas. Ongoing advances in computer science and robotics have led to applications for covering large areas that require coordinated tasks by multiple control programs including robots. Our study aims at coordination and cooperation by multiple agents, and we discuss it using an example of the cleaning tasks to be performed by multiple agents with potentially different performances and capabilities. We then developed a method for partitioning the target area on the basis of their performances in order to improve the overall efficiency through their balanced collective efforts. Agents, i.e., software for controlling devices and robots, autonomously decide in a cooperative manner how the task/area is partitioned by taking into account the characteristics of the environment and the differences in agents' software capability and hardware performance. During this partitioning process, agents also learn the locations of obstacles and the probabilities of dirt accumulation that express what areas are easy to be dirty. Experimental evaluation showed that even if the agents use different algorithms or have the batteries with different capacities resulting in different performances, and even if the environment is not uniform such as different locations of easy-to-dirty areas and obstacles, the proposed method can adaptively partition the task/area among the agents with the learning of the probabilities of dirt accumulations. Thus, agents with the proposed method can keep the area clean effectively and evenly.

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Section: Related Workmentioning

confidence: 99%

Section: Environmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Coordinated Area Partitioning Method by Autonomous Agents for Continuous Cooperative Tasks

Sea

Kato

Sugawara

2017

Journal of Information Processing

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“…One remarkable difference consists in the pre-defined targets of our problem that require to be in different sets. Elor and Bruckstein [11] propose an Ant-Colony algorithm for graph partitioning and patrolling based on the behavior of gas filled balloons that reaches balanced partitions in linear time on average.…”

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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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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“…In [2], the authors introduce a multi-agent patrolling algorithm based on a physical analogy: gas-filled balloons. A very interesting article is [3], in which a multi-agent cooperative solution is realized, that is robust and can deal with perimeter changes.…”

Section: Introductionmentioning

confidence: 99%

Distributed perimeter patrolling and tracking for camera networks

Baseggio

Cenedese

Merlo

et al. 2010

49th IEEE Conference on Decision and Control (CDC)

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In this work, we propose a distributed control strategy for perimeter patrolling and target tracking in a multi-camera video surveillance system with communication, resources and speed constraints. These cameras are required to monitor a perimeter and share common portions of this perimeter to allow redundant coverage. We propose an algorithm that is able to find the global patrolling strategy only through local asynchronous communication and coordination of neighboring cameras even in presence of physical limits of each camera visibility area. The algorithm converges to an optimal solution, and its distributed implementation is obtained through an electric circuit analogy. The proposed system also includes a Kalman-based filter for each camera to track moving targets within its areas of competence, and a distributed coordination scheme for target hand-off between different cameras that guarantees target locking at all times. Numerical simulations are provided to test the proposed algorithms

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Multi-a(ge)nt Graph Patrolling and Partitioning

Cited by 27 publications

References 8 publications

Coordinated Area Partitioning Method by Autonomous Agents for Continuous Cooperative Tasks

Coordinated Area Partitioning Method by Autonomous Agents for Continuous Cooperative Tasks

External Coordination Media in Capacity-Constrained Multiagent Systems

Distributed perimeter patrolling and tracking for camera networks

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