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8,455
Consensus Problems in Networks of Agents with Switching Topology and Time-Delays
, 2003
"... In this paper, we discuss consensus problems for a network of dynamic agents with fixed and switching topologies. We analyze three cases: i) networks with switching topology and no time-delays, ii) networks with fixed topology and communication time-delays, and iii) max-consensus problems (or leader ..."
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Cited by 1112 (21 self)
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In this paper, we discuss consensus problems for a network of dynamic agents with fixed and switching topologies. We analyze three cases: i) networks with switching topology and no time-delays, ii) networks with fixed topology and communication time-delays, and iii) max-consensus problems (or
Consensus and cooperation in networked multi-agent systems
- Proceedings of the IEEE
, 2007
"... Summary. This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An ove ..."
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Cited by 807 (4 self)
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Summary. This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees
A theory of timed automata
, 1999
"... Model checking is emerging as a practical tool for automated debugging of complex reactive systems such as embedded controllers and network protocols (see [23] for a survey). Traditional techniques for model checking do not admit an explicit modeling of time, and are thus, unsuitable for analysis of ..."
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Cited by 2651 (32 self)
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Model checking is emerging as a practical tool for automated debugging of complex reactive systems such as embedded controllers and network protocols (see [23] for a survey). Traditional techniques for model checking do not admit an explicit modeling of time, and are thus, unsuitable for analysis
Optimization Flow Control, I: Basic Algorithm and Convergence
- IEEE/ACM TRANSACTIONS ON NETWORKING
, 1999
"... We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm. In thi ..."
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Cited by 694 (64 self)
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We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm
A Case for End System Multicast
- in Proceedings of ACM Sigmetrics
, 2000
"... Abstract — The conventional wisdom has been that IP is the natural protocol layer for implementing multicast related functionality. However, more than a decade after its initial proposal, IP Multicast is still plagued with concerns pertaining to scalability, network management, deployment and suppor ..."
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Cited by 1290 (24 self)
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-to-end delays than IP Multicast. In this paper, we study these performance concerns in the context of the Narada protocol. In Narada, end systems selforganize into an overlay structure using a fully distributed protocol. Further, end systems attempt to optimize the efficiency of the overlay by adapting
Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
"... A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrate-and-fire neurons in real-time. We propose a new computational model for real-time computing on time-var ..."
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Cited by 469 (38 self)
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-varying input that provides an alternative to paradigms based on Turing machines or attractor neural networks. It does not require a task-dependent construction of neural circuits. Instead it is based on principles of high dimensional dynamical systems in combination with statistical learning theory, and can
A Model of Saliency-based Visual Attention for Rapid Scene Analysis
, 1998
"... A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing salie ..."
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Cited by 1748 (72 self)
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A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing
The synchronous dataflow programming language LUSTRE
- Proceedings of the IEEE
, 1991
"... This paper describes the language Lustre, which is a dataflow synchronous language, designed for programming reactive systems --- such as automatic control and monitoring systems --- as well as for describing hardware. The dataflow aspect of Lustre makes it very close to usual description tools in t ..."
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Cited by 646 (50 self)
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in these domains (block-diagrams, networks of operators, dynamical samples-systems, etc: : : ), and its synchronous interpretation makes it well suited for handling time in programs. Moreover, this synchronous interpretation allows it to be compiled into an efficient sequential program. Finally, the Lustre
Dynamic Power Allocation and Routing for Time Varying Wireless Networks
- IEEE Journal on Selected Areas in Communications
, 2003
"... We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be tran ..."
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Cited by 358 (73 self)
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We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues
Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding
- Advances in Neural Information Processing Systems 8
, 1996
"... On large problems, reinforcement learning systems must use parameterized function approximators such as neural networks in order to generalize between similar situations and actions. In these cases there are no strong theoretical results on the accuracy of convergence, and computational results have ..."
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Cited by 433 (20 self)
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On large problems, reinforcement learning systems must use parameterized function approximators such as neural networks in order to generalize between similar situations and actions. In these cases there are no strong theoretical results on the accuracy of convergence, and computational results
Results 1 - 10
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8,455