The goal of decentralized optimization over a network is to optimize a global objective formed by a sum of local (possibly nonsmooth) convex functions using only local computation and communication. It arises in vario...
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The goal of decentralized optimization over a network is to optimize a global objective formed by a sum of local (possibly nonsmooth) convex functions using only local computation and communication. It arises in various application domains, including distributed tracking and localization, multi-agent coordination, estimation in sensor networks, and large-scale machine learning. We develop and analyze distributed algorithms based on dual subgradient averaging, and we provide sharp bounds on their convergence rates as a function of the network size and topology. Our analysis allows us to clearly separate the convergence of the optimization algorithm itself and the effects of communication dependent on the network structure. We show that the number of iterations required by our algorithm scales inversely in the spectral gap of the network, and confirm this prediction's sharpness both by theoretical lower bounds and simulations for various networks. Our approach includes the cases of deterministic optimization and communication, as well as problems with stochastic optimization and/or communication.
In the past decade, urban traffic has increased tremendously. As a result, the urban population has to invest more time in traveling. Increased road traffic results in an increased number of road accidents and more co...
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ISBN:
(纸本)9781509013388
In the past decade, urban traffic has increased tremendously. As a result, the urban population has to invest more time in traveling. Increased road traffic results in an increased number of road accidents and more consumption of fuel, thus wasting energy. Hence for solving this issue, this paper proposes a traffic signal synchronization system which takes real time traffic signal data as input and with the implementation of multi-agent fuzzy logic, it introduces the design of an intelligent system which would smoothen the overall road traffic of the city. Fuzzy system is capable of handling the various levels of uncertainties found in the input data taken from the traffic signals. Since fuzzy logic system needs expert knowledge for its rule base and the rule base remains unchanged once defined, this paper adds up Q-learning module so that the system learns by itself by updating the set of rule base.
The multi-agent research community is currently faced with a paradox. While promoting the use of agents as the silver bullet for various software engineering problems, it faces difficulties in presenting successful de...
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ISBN:
(纸本)1402005636
The multi-agent research community is currently faced with a paradox. While promoting the use of agents as the silver bullet for various software engineering problems, it faces difficulties in presenting successful deployments. Despite the countless multi-agent prototypes that have been developed, the number of actually deployed and in use MAS is at best very small (Gasser 2000). And as long as multi-agent frameworks continue to encounter difficulties in scaling up, it seems unlikely that this will change. This paper has two aims. First, it is an attempt to relate the scalability problem of multi-agentsystems with that of executing large numbers of concurrent threads. Second, it evaluates a CORBA/Java middle-ware layer for transparent access to distributed resources. Using such a layer, it is possible, to build multi-agentsystems that require large numbers of concurrent threads and significant memory resources.
This paper investigates the containment control problem in distributed multi-agent systems under switching topologies. We propose a distributed containment control algorithm to address scenarios where different types ...
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This paper investigates the containment control problem in distributed multi-agent systems under switching topologies. We propose a distributed containment control algorithm to address scenarios where different types of agents coexist within the system (heterogeneous multi-agentsystem). The algorithm ensures that all agents within the system will enter the convex hull formed by leaders. Additionally, we improve the handling of leader information by directly computing it, which avoids the computational overhead associated with traditional algorithms that involve projection calculations. By discussing system stability and convergence under three different conditions, we prove that each follower can enter the convex hull ultimately if the union of each switching graph is strongly connected in a bounded time interval. Finally, we validate the effectiveness of the proposed algorithm through a numerical simulation.
Conducting data fusion and Command and Control (C2) in large-scale systems requires more than the presently available Peer-to-Peer (P2P) technologies provide. Resource Clustered Chord (RC-Chord) is an extension to the...
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ISBN:
(纸本)9781424452385
Conducting data fusion and Command and Control (C2) in large-scale systems requires more than the presently available Peer-to-Peer (P2P) technologies provide. Resource Clustered Chord (RC-Chord) is an extension to the Chord protocol that incorporates elements of a hierarchical peer-to-peer architecture to facilitate coalition formation algorithms in large-scale systems. Each cluster in this hierarchy represents a particular resource available for allocation, and RC-Chord provides the capabilities to locate agents of a particular resource. This approach improves upon other strategies by including support for abundant resources, or those resources that most or all agents in the system possess. This scenario exists in large-scale coalition formation problems, and applies directly to the United States Air Force's CyberCraft project. Simulations demonstrate that RC-Chord scales to systems of one million or more agents, and can be adapted to serve as a deployment environment for CyberCraft.
This paper presents a zero-idle pipeline scheduling model for distributed multi-agent systems. The petri net model of the system can be obtained intuitively. The agent pipeline scheduling model is extended by the codi...
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Existing task allocation algorithms often fail to consider communication load and do not meet the scalability requirements of large-scale systems in practical applications. Furthermore, many general network simplifica...
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Existing task allocation algorithms often fail to consider communication load and do not meet the scalability requirements of large-scale systems in practical applications. Furthermore, many general network simplification algorithms are centralized and not designed for task allocation scenarios, thus losing their superiority when applied to solve task allocation problems in distributedsystems. Inspired by recent network simplification algorithms, this paper introduces a novel network simplification algorithm called bid -based distributed brokenmotifs (BDBM), which simplifies the communication network by reducing the number of closed -loop triangles. The BDBM algorithm keeps those communication edges that facilitate the deconfliction based on the initial bids, thus avoiding the surge in the number of convergence iterations caused by the simplification. In addition, CBBA is distributed and requires only two iterations to complete the communication network simplification. Theoretical analysis confirms that the simplified network of BDBM remains connected and can be used in combination with improved task allocation algorithms based on consensus -based bundle algorithm (CBBA). In terms of experiments, we conducted comprehensive experiments in different settings and found that the proposed algorithm does not lead to worse allocation solutions. The statistical results also show that BDBM outperforms state-of-the-art network simplification algorithms in terms of solving efficiency and scalability in assisting CBBA solve large-scale complex task allocation problems.
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