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47
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 70 (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.
Emergence of collective behavior in evolving populations of flying agents
 in Genetic and Evolutionary Computation Conference (GECCO2003
, 2003
"... Abstract. We demonstrate the emergence of collective behavior in two evolutionary computation systems, one an evolutionary extension of a classic (highly constrained) flocking algorithm and the other a relatively unconstrained system in which the behavior of agents is governed by evolved computer p ..."
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Cited by 65 (8 self)
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Abstract. We demonstrate the emergence of collective behavior in two evolutionary computation systems, one an evolutionary extension of a classic (highly constrained) flocking algorithm and the other a relatively unconstrained system in which the behavior of agents is governed by evolved computer programs. We describe the systems in detail, document the emergence of collective behavior, and argue that these systems present new opportunities for the study of group dynamics in an evolutionary context. 1
Interactive Behaviors for Bipedal Articulated Figures.” Computer Graphics 25(4
, 1991
"... We describe techniques for interactively controlling bipedal articulated figures through kinematic constraints. These constraints model certain behavioral tendencies which capture some of the characteristics of humanlike movement, and give us control over such elements as the figures ' balance ..."
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Cited by 48 (15 self)
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We describe techniques for interactively controlling bipedal articulated figures through kinematic constraints. These constraints model certain behavioral tendencies which capture some of the characteristics of humanlike movement, and give us control over such elements as the figures ' balance and stability. They operate in near realtime, so provide behavioral control for interactive manipulation. These constraints form the basis of an interactive motiongeneration system that allows the active movement elements to be layered on top of the passive behavioral constraints.
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 34 (6 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
Distributed coordination architecture for multirobot formation control
"... In the exploration and implementation of formation control strategies, communication range and bandwidth limitations form a barrier to large scale formation control applications. The limitations of current formation control strategies involving a leader–follower approach and a consensusbased approa ..."
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Cited by 26 (2 self)
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In the exploration and implementation of formation control strategies, communication range and bandwidth limitations form a barrier to large scale formation control applications. The limitations of current formation control strategies involving a leader–follower approach and a consensusbased approach with fully available group trajectory information are explored. A unified, distributed formation control architecture that accommodates an arbitrary number of group leaders and arbitrary information flow among vehicles is proposed. The architecture requires only local neighbortoneighbor information exchange. In particular, an extended consensus algorithm is applied on the group level to estimate the timevarying group trajectory information in a distributed manner. Based on the estimated group trajectory information, a consensusbased distributed formation control strategy is then applied for vehicle level control. The proposed architecture is experimentally implemented and validated on a multirobot platform under local neighbortoneighbor information exchange with a single or multiple leaders involved. c ○ 2007 Elsevier B.V. All rights reserved.
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 25 (8 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 25 (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 22 (7 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 16 (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.
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 14 (6 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.