Collective Behavior of Dynamic Swarm with General Topology and Complex Communication Time-Delays
This paper presents a complex interaction delayed swarm model with a general topology to study the collective behavior of a group of autonomous agents using the nearest neighbor rulers in the presence of communication delays. It is proved that under certain conditions the swarm members will converge to a finite region around the swarm weighted center and move together in a cohesive cluster following the motion of the weighted center. For general cases, the delayed swarm may display more complex dynamics, including oscillation and divergence, depending on the delay values. This suggests that the time delay may have significant consequence in the collective dynamics of swarms.

title: Complex Analysis of Anisotropic Swarms with Gaussian Profiles
abstract: This paper considers an M-member "individual-based" continuous time swarm model with individuals moving with a nutrient profile (or an attractant/repellent) in an n- dimensional space. It is proved that the swarm members aggregate and eventually form a cohesive cluster of finite size for Gaussian Profiles. Moreover, all the swarm members will converge to more favorable areas of the Gaussian profile under certain conditions.

title: Collective Behavior Analysis of a Class of Social Foraging Swarms
abstract: This paper considers an anisotropic swarm model that consists of a group of mobile autonomous agents with an attraction-repulsion function that can guarantee collision avoidance between agents and a Gaussian-type attractant/repellent nutrient profile. The swarm behavior is a result of a balance between inter-individual interplays as well as the interplays of the swarm individuals (agents) with their environment. It is proved that the members of a reciprocal swarm will aggregate and eventually form a cohesive cluster of finite size. It is shown that the swarm system is completely stable, that is, every solution converges to the equilibrium point set of the system. Moreover, it is also shown that all the swarm individuals will converge to more favorable areas of the Gaussian profile under certain conditions. The results of this paper provide further insight into the effect of the interaction pattern on self-organized motion for a Gaussian-type attractant/repellent nutrient profile in a swarm system.

title: Complex Analysis of Anisotropic Swarms
abstract: This paper considers a continuous time swarm model with individuals moving with a nutrient profile (or an attractant/repellent) in an n-dimensional space. The swarm behavior is a result of a balance between inter-individual interplays as well as the interplays of the swarm agents with their environment. It is proved that the swarm members aggregate and eventually form a cohesive cluster of finite size around the swarm weighted center in a finite time under certain conditions.

title: Flocking of Multi-Vehicle Systems With A Leader
abstract: We study the coordinated motion of a group of vehicles with a leader based on nearest neighbor rules. The leader may be a special vehicle in the group or an external signal (virtual leader) to steer the vehicle group. The control law consists of two parts: a potential field force that makes the vehicles attract to each other and at the same time avoid collision in the group, and an alignment force that makes all vehicles' headings and speeds to converge respectively to common values. We assume that the interaction patterns are either fixed or switching based on the information topologies of the leader and member vehicles. Our approach is based on the Lyapunov theory and basic graph theory. We also consider the effect of noise on the collective dynamics of the group. Numerical simulations are worked out to illustrate the analytical results

title: Controllability of a Leader-Follower Dynamic Network with Interaction Time Delays
abstract: This paper studies the controllability of a leader-follower network of dynamic agents in the presence of communication delays. The network dynamics is governed by nearest neighbor rules over a fixed communication topology. The leader is a particular agent acting as an external input to steer the other member agents. We derive sufficient conditions of the controllability of the dynamic network and give an example to illustrate the main results.

title: The dynamics of a prey-dependent consumption model concerning impulsive control strategy
abstract: A mathematical model for dynamics of a prey-dependent consumption model concerning impulsive control strategy is proposed and analyzed. We show that there exists a globally stable pest-eradication periodic solution when the impulsive period is less than some critical values. Further, the conditions for the permanence of system are given. We show the existence of nontrivial periodic solution if the pest-eradication periodic solution loses its stability. When the unique positive periodic solution lose its stability, numerical simulation shows there is a characteristic sequence of bifurcations, leading to a chaotic dynamics, which implies that the impulsive control model we considered has more complex dynamics including period-doubling bifurcation, symmetry-breaking bifurcation, period-halving bifurcation, quasi-periodic oscillation and chaos.

title: A Novel Worm Detection Model Based on Host Packet Behavior Ranking
abstract: Traditional behavior-based worm detection can't eliminate the influence of the worm-like P2P traffic effectively, as well as detect slow worms. To try to address these problems, this paper first presents a user habit model to describe the factors which influent the generation of network traffic, then a design of HPBRWD (Host Packet Behavior Ranking Based Worm detection) and some key issues about it are introduced. This paper has three contributions to the worm detection: 1) presenting a hierarchical user habit model; 2) using normal software and time profile to eliminate the worm-like P2P traffic and accelerate the detection of worms; 3) presenting HPBRWD to effectively detect worms. Experiments results show that HPBRWD is effective to detect worms.

title: Measuring the meaning in time series clustering of text search queries
abstract: We use a combination of proven methods from time series analysis and machine learning to explore the relationship between temporal and semantic similarity in web query logs; we discover that the combination of correlation and cycles is a good, but not perfect, sign of semantic relationship.

title: Improved Differential Evolution with Dynamic Population Size
abstract: As a novel evolutionary computing technique, recently Differential Evolution (DE) has attracted much attention and wide applications due to its simple concept and easy implementation. However, all the control parameters of the classic DE (crossover rate, scaling factor, and population size) keep fixed during the searching process. To improve the performance of DE, an improved DE (IDE) with dynamic population size is proposed in this paper. Simulation results and comparisons based on some well-known benchmarks and an IIR design problem show the good efficiency of the proposed IDE.

title: Integrating rules and constraints
abstract: Constraint satisfaction problem (CSP) is a deductive problem of a special kind, while rule-based systems are the practical programs that have implemented many of the ideas and techniques of deductive systems. Incorporating CSP into a rule-based system allows the rule-based system to exploit the power of CSP techniques in handling this special class of problems. This paper shows how constraints and rules can be integrated. This integration also helps to deal with the problems of disjunctions, which are not handled satisfactorily in the current rule-based systems.<<ETX>>