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26
Go to the ant: engineering principles from natural multi agent systems. Annls Ops Res
, 1997
"... Agent architectures need to organize themselves and adapt dynamically to changing circumstances without topdown control from a system operator. Some researchers provide this capability with complex agents that emulate human intelligence and reason explicitly about their coordination, reintroducing ..."
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Cited by 51 (1 self)
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Agent architectures need to organize themselves and adapt dynamically to changing circumstances without topdown control from a system operator. Some researchers provide this capability with complex agents that emulate human intelligence and reason explicitly about their coordination, reintroducing many of the problems of complex system design and implementation that motivated increasing software localization in the first place. Naturally occurring systems of simple agents (such as populations of insects or other animals) suggest that this retreat is not necessary. This paper summarizes several studies of such systems, and derives from them a set of general principles that artificial multiagent systems can use to support overall system behavior significantly more complex than the behavior of the individuals agents. 1.
Distributed consensus algorithms in sensor networks with communication channel noise and random link failures
 in Proc. 41st Asilomar Conf. Signals, Systems, Computers
, 2007
"... Abstract—The paper studies average consensus with random topologies (intermittent links) and noisy channels. Consensus with noise in the network links leads to the biasvariance dilemma—running consensus for long reduces the bias of the final average estimate but increases its variance. We present t ..."
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Cited by 43 (13 self)
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Abstract—The paper studies average consensus with random topologies (intermittent links) and noisy channels. Consensus with noise in the network links leads to the biasvariance dilemma—running consensus for long reduces the bias of the final average estimate but increases its variance. We present two different compromises to this tradeoff: the algorithm modifies conventional consensus by forcing the weights to satisfy a persistence condition (slowly decaying to zero;) and the algorithm where the weights are constant but consensus is run for a fixed number of iterations, then it is restarted and rerun for a total of runs, and at the end averages the final states of the runs (Monte Carlo averaging). We use controlled Markov processes and stochastic approximation arguments to prove almost sure convergence of to a finite consensus limit and compute explicitly the mean square error (mse) (variance) of the consensus limit. We show that represents the best of both worlds—zero bias and low variance—at the cost of a slow convergence rate; rescaling the weights balances the variance versus the rate of bias reduction (convergence rate). In contrast, , because of its constant weights, converges fast but presents a different biasvariance tradeoff. For the same number of iterations, shorter runs (smaller) lead to high bias but smaller variance (larger number of runs to average over.) For a static nonrandom network with Gaussian noise, we compute the optimal gain for to reach in the shortest number of iterations, with high probability (1), ()consensus ( residual bias). Our results hold under fairly general assumptions on the random link failures and communication noise. Index Terms—Additive noise, consensus, sensor networks, stochastic approximation, random topology. I.
Selfimproving algorithms
 in SODA ’06: Proceedings of the seventeenth annual ACMSIAM symposium on Discrete algorithm
"... We investigate ways in which an algorithm can improve its expected performance by finetuning itself automatically with respect to an arbitrary, unknown input distribution. We give such selfimproving algorithms for sorting and computing Delaunay triangulations. The highlights of this work: (i) an al ..."
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Cited by 26 (4 self)
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We investigate ways in which an algorithm can improve its expected performance by finetuning itself automatically with respect to an arbitrary, unknown input distribution. We give such selfimproving algorithms for sorting and computing Delaunay triangulations. The highlights of this work: (i) an algorithm to sort a list of numbers with optimal expected limiting complexity; and (ii) an algorithm to compute the Delaunay triangulation of a set of points with optimal expected limiting complexity. In both cases, the algorithm begins with a training phase during which it adjusts itself to the input distribution, followed by a stationary regime in which the algorithm settles to its optimized incarnation. 1
Robot Soccer with LEGO Mindstorms
, 1999
"... We have made a robot soccer model using LEGO Mindstorms robots, which was shown at RoboCup98 during the World Cup in soccer in France 1998. We developed the distributed behaviourbased approach in order to make a robust and high performing robot soccer demonstration. Indeed, our robots scored in an ..."
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Cited by 21 (5 self)
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We have made a robot soccer model using LEGO Mindstorms robots, which was shown at RoboCup98 during the World Cup in soccer in France 1998. We developed the distributed behaviourbased approach in order to make a robust and high performing robot soccer demonstration. Indeed, our robots scored in an average of 7580constructed a stadium out of LEGO pieces, including stadium light, rolling commercials, moving cameras projecting images to big screens, scoreboard and approximately 1500 small LEGO spectators who made the "Mexican wave" as known from soccer stadiums. These devices were controlled using the LEGO Dacta Control Lab system and the LEGO CodePilot system that allow programming motor reactions which can be based on sensor inputs. The wave of the LEGO spectators was made using the principle of emergent behaviour. There was no central control of the wave, but it emerges from the interaction between small units of spectators with a local feedback control. 1 Introduction Before the LE...
Modeling and Visualization of Biological Structures
 In Proceeding of Graphics Interface
, 1993
"... Rapid progress in the modeling of biological structures and simulation of their development has occurred over the last few years. It has been coupled with the visualization of simulation results, which has lead to a better understanding of morphogenesis and given rise to new procedural techniques fo ..."
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Cited by 20 (2 self)
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Rapid progress in the modeling of biological structures and simulation of their development has occurred over the last few years. It has been coupled with the visualization of simulation results, which has lead to a better understanding of morphogenesis and given rise to new procedural techniques for realistic image synthesis. This paper characterizes selected models of morphogenesis with a significant visual component. KEYWORDS: developmental models in biology, morphogenesis, simulation and visualization of biological phenomena, realistic image synthesis, reactiondiffusion, diffusionlimited growth, cellular automaton, Lsystem. How far mathematics will suffice to describe, and physics to explain, the fabric of the body, no man can forsee. D'Arcy Thompson, On Growth and Form [40]
A study on decentralized receding horizon control for decoupled systems
, 2004
"... Abstract — We consider a set of decoupled dynamical systems and an optimal control problem where cost function and constraints couple the dynamical behavior of the systems. The coupling is described through a connected graph where each system is a node and, cost and constraints of the optimization p ..."
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Cited by 14 (4 self)
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Abstract — We consider a set of decoupled dynamical systems and an optimal control problem where cost function and constraints couple the dynamical behavior of the systems. The coupling is described through a connected graph where each system is a node and, cost and constraints of the optimization problem associated to each node are only function of its state and the states of its neighbors. For such scenario, we propose a framework for designing decentralized Receding Horizon Control (RHC) control schemes. In these decentralized schemes, a centralized RHC controller is broken into distinct RHC controllers of smaller sizes. Each RHC controller is associated to a different node and computes the local control inputs based only on the states of the node and of its neighbors. The proposed decentralized control schemes are formulated in a rigorous mathematical framework. Moreover, we highlight the main issues involved in guaranteeing stability and constraint fulfillment for such schemes and the degree of conservativeness that the decentralized approach introduces. I.
A Swarmbased Fuzzy Logic Control Mobile Sensor Network for Hazardous Contaminants Localization
 In Proceedings of the IEEE International Conference on Mobile Adhoc and Sensor Systems (MASS’04
, 2004
"... In this paper, we describe a swarmbased fuzzy logic control (FLC) mobile sensor network approach for collaboratively locating the hazardous contaminants in an unknown largescale area. The mobile sensor network is composed of a collection of distributed nodes (robots), each of which has limited sen ..."
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Cited by 10 (0 self)
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In this paper, we describe a swarmbased fuzzy logic control (FLC) mobile sensor network approach for collaboratively locating the hazardous contaminants in an unknown largescale area. The mobile sensor network is composed of a collection of distributed nodes (robots), each of which has limited sensing, intelligence and communication capabilities. An adhoc wireless network is established among all nodes, and each node considers other nodes as extended sensors. By gathering other nodes ’ locations and measurement data, each node’s FLC can independently determine its next optimal deployment location. Simultaneously, by applying the three properties of the swarm behavior: separation, cohesion and alignment, the approach can ensure the sensor network attains wide regional coverage and dynamically stable connectivity. The simulation presented in this paper shows the swarmbased FLC mobile sensor network can achieve better performance and have higher fault tolerance in the event of partial node failures and sensor measurement errors. 1.
Swarming behavior using probabilistic roadmap techniques
 Lecture Notes in Computer Science
, 2005
"... Abstract. While techniques exist for simulating swarming behaviors, these methods usually provide only simplistic navigation and planning capabilities. In this review, we explore the benefits of integrating roadmapbased path planning methods with flocking techniques to achieve different behaviors. W ..."
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Cited by 6 (1 self)
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Abstract. While techniques exist for simulating swarming behaviors, these methods usually provide only simplistic navigation and planning capabilities. In this review, we explore the benefits of integrating roadmapbased path planning methods with flocking techniques to achieve different behaviors. We show how group behaviors such as exploring can be facilitated by using dynamic roadmaps (e.g., modifying edge weights) as an implicit means of communication between flock members. Extending ideas from cognitive modeling, we embed behavior rules in individual flock members and in the roadmap. These behavior rules enable the flock members to modify their actions based on their current location and state. We propose new techniques for several distinct group behaviors: homing, exploring (covering and goal searching), passing through narrow areas and shepherding. We present results that show that our methods provide significant improvement over methods that utilize purely local knowledge and moreover, that we achieve performance approaching that which could be obtained by an ideal method that has complete global knowledge. Animations of these behaviors can be viewed on our webpages. 1
Simulation of Large Crowds in Emergency Situations Including Gaseous Phenomena
 in IEEE Computer Graphics International. 2005
"... Crowd animation and simulation have been widely studied over the last decade for many purposes: populating collaborative virtual environments, entertainment and special effects industry and finally simulating behaviors and motion of people in emergency situations for safety systems. This last topic ..."
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Cited by 6 (0 self)
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Crowd animation and simulation have been widely studied over the last decade for many purposes: populating collaborative virtual environments, entertainment and special effects industry and finally simulating behaviors and motion of people in emergency situations for safety systems. This last topic is addressed in this paper. We propose an original enhancement of a well known physicsbased animation model which allows to consider influence of gaseous phenomena such as smoke or toxic gases in the behavior of the crowd. In order to get real time performances we also propose an implementation of this framework on modern graphics hardware, which allows to simulate crowds of thousands individuals at interactive framerate. 1
The Convergence of Bird Flocking
, 2009
"... We bound the time it takes for a group of birds to reach steady state in a standard flocking model. We prove that (i) within single exponential time fragmentation ceases and each bird settles on a fixed flying direction; (ii) the flocking network converges only after a number of steps that is an ite ..."
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Cited by 6 (2 self)
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We bound the time it takes for a group of birds to reach steady state in a standard flocking model. We prove that (i) within single exponential time fragmentation ceases and each bird settles on a fixed flying direction; (ii) the flocking network converges only after a number of steps that is an iterated exponential of height logarithmic in the number of birds. We also prove the highly surprising result that this bound is optimal. The model directs the birds to adjust their velocities repeatedly by averaging them with their neighbors within a fixed radius. The model is deterministic, but we show that it can tolerate a reasonable amount of stochastic or even adversarial noise. Our methods are highly general and we speculate that the results extend to a wider class of models based on undirected flocking networks, whether defined metrically or topologically. This work introduces new techniques of broader interest, including the flight net, the iterated spectral shift, and a certain residueclearing argument in circuit complexity.