Coordination learning in stag hunt games with application to emergency management

Response teams for natural disaster emergencies require coordinated and self-organized efforts for rescue, medical services, damage containment, and evacuation. The unfolding of events depends on initial conditions of specific time, location, and preparedness of the response teams. This study considered a new range of emergency response situations where the perpetrator is a sentient attacker that learns with repeated exchanges. The strategy is conceptualized as a stag hunt coordination game on the part of the defense agents and a strictly competitive game with respect to the attacking adversary. Participants were 28 university students who played an iterative board game (The Creature that Ate Sheboygan) wherein a team of three Humans represented military and civil resources, against one Godzilla-type monster. The Monster gained points by destroying buildings and human combat power. The Humans gained points by wearing down the Monster's defenses and containing damage caused by the Monster. Experimental manipulations and empirical analysis showed the following: Communication outages among the Humans assisted the Monster, but the ability to communicate only equalized the Humans' chances rather than providing them with an advantage. Coordination among Humans was instant, but it fluctuated greatly as a result of the Monster's progress. Nonlinear analysis showed an asymptotic decline in coordination to a non-zero level in response to outcome uncertainty. Learning effects were noted for Humans and Monsters, but there were significant interactions with communication blackout conditions     

Nonlinear pedagogy: a constraints-led framework for understanding emergence of game play and movement skills

Team sport competition can be characterized as a complex adaptive system in which concepts from nonlinear dynamics can provide a sound theoretical framework to understand emergent behavior such as movement coordination and decision making in game play. Nonlinear Pedagogy is presented as a methodology for games teaching, capturing how phenomena such as movement variability, self-organization, emergent decision making, and symmetry-breaking occur as a consequence of interactions between agent-agent and agent-environment constraints. Empirical data from studies of basketball free-throw shooting and dribbling are used as task vehicles to exemplify how nonlinear phenomena characterize game play in sport. In this paper we survey the implications of these data for Nonlinear Pedagogy, focusing particularly on the manipulation of constraints in team game settings. The data and theoretical modeling presented in this paper provide a rationale in nonlinear dynamics for the efficacy of a prominent model of game play teaching, Teaching Games for Understanding approach.     

Bottom-Up Consensus Formation in Voting Games

The dynamics of positions of political parties have been extensively studied by both numerical and agent-based approaches. We focus on the dynamics of formation and division of parties, particularly on how game rules to determine a winning party influences the agents' decision-making and process to reaching a consensus, and we perform an agent-based simulation using a game model called Spatial Voting Game. In this paper, we briefly describe the game as an environment of our agent-based simulation and learning architecture of agents for adaptive players in a multiagent system. Then we present simulation results showing that the players' strategies acquired by evolutionary operator and the process to form parties in a negotiation are different according to the game rules.     

Distributed adaptive tracking control of multiple flexible spacecraft under various actuator and measurement limitations

This paper investigates the distributed leader–follower tracking problem for a team of flexible spacecraft over an undirected communication network with uncertain parameters subject to various actuator and measurement limitations. Assuming that at least one team member can receive information from the virtual leader, three scenarios are considered: (i) all the states of the flexible spacecraft can be completely measured and driven, (ii) only the rigid part of the flexible spacecraft can be driven with full state feedback and (iii) only the rigid part of the flexible spacecraft can be measured and driven. In the first case, a continuous adaptive control law is designed by building a unified architecture based on the linear-in-parameter property. In the second case, a distributed adaptive control algorithm is developed with a discontinuous parameter update law by treating the team of flexible spacecraft as two cascading subsystems. In the third case, a distributed adaptive control law is established with feedback from the generalized coordinates, generalized velocities and generalized accelerations of the rigid part of the spacecraft. It is theoretically proved that the closed-loop systems under the three designed adaptive control laws are all convergent to the target states. Finally, three numerical examples are presented to illustrate the effectiveness of the three proposed control laws.     

Non-linear differential game with on-line identified opposition

The Liapunov Design Technique and the theory of adaptive identifiers are used to provide the deterministic on-line state (feedback) information and the information on the opponent's control to each of the players in the competitive two-person zero-sum non-linearizable differential game. To this aim the identifier theory is extended to the case of time-varying parameters, and a new approach without the standard “error-equation” is adopted to handle the non-linearity. The information provided is of prescribed accuracy and obtainable in prescribed time. The identifiers constructed allow to attain the standard objectives: playability for collision with a target, possibly (permanent) capture there, avoidance of an anti-target and min-max of a given cost functional. The Luenberger-type observers for a linear game follow as a particular case. The method is illustrated by an example.     

半封闭空间明火引燃油气特性实验

为研究明火引燃油气着火爆炸特性,建立了半封闭着火爆炸实验平台。通过高速摄影仪拍摄的火焰图像,研究不同油气体积分数下的火焰传播特性。根据高频压力传感器采集的容器内压力变化情况,分析不同油气体积分数下的压力发展特性。结果表明,油气体积分数对火焰组分、火焰传播速度、压力和压力变化速率有显著影响;火焰具有明显的分区现象,可分为燃烧核和火焰阵面,并且纵向火焰阵面速度大于横向火焰阵面速度;容器内压力发展历程可分为4个阶段,而且会形成压力双峰现象;油气爆炸过程中,火焰结构与压力波形成了强烈的耦合作用。     

Diffusion Mass Transfer in Miscible Oil Recovery: Visual Experiments and Simulation

Co-and counter-current type transfers due to diffusion and -free- convection caused by the buoyant forces between fracture and matrix were studied experimentally using 2-D glass-bead models. Mineral oil and kerosene were used as the displaced phase. The model saturated with oil was exposed to solvent phase (pentane) under static conditions (no flow in fracture) to mimic matrix-fracture interaction during gas or liquid solvent injection in naturally fractured reservoirs. Displacement fronts and patterns were analyzed and quantified using fractal techniques to obtain correlations between the fractal properties and displacement type. Displacements resulted in a mixture of bulk diffusion and -free- convection mainly depending on the interaction type (co- or counter-current), oil type, and displacement direction (horizontal and vertical). Conditions yielding different types of displacement patterns were identified. Finally, a stochastic model that was inspired from invasion percolation and diffusion limited aggregation algorithms was developed for the horizontal displacement cases. The experimental observations were matched to the displacement patterns obtained through the stochastic modeling.     

Finite Element Analysis of Shape Memory Alloy Adaptive Trusses with Geometrical Nonlinearities

This contribution deals with the nonlinear analysis of shape memory alloy (SMA) adaptive trusses employing the finite element method. Geometrical nonlinearities are incorporated into the formulation together with a constitutive model that describes different thermomechanical behaviors of SMA. It has four macroscopic phases (three variants of martensite and an austenitic phase), and considers different material properties for austenitic and martensitic phases together with thermal expansion. An iterative numerical procedure based on the operator split technique is proposed in order to deal with the nonlinearities in the constitutive formulation. This procedure is introduced into ABAQUS as a user material routine. Numerical simulations are carried out illustrating the ability of the developed model to capture the general behavior of shape memory bars. After that, it is analyzed the behavior of some adaptive trusses built with SMA actuators subjected to different thermomechanical loadings.     

Neimark–Sacker bifurcation analysis and complex nonlinear dynamics in a heterogeneous quadropoly game with an isoelastic demand function

In this paper, a nonlinear quadropoly game based on Cournot model with fully heterogeneous players is established. This game extends the model introduced by Tramontana and Elsadany (Nonlinear Dyn 68:187–193, 2012) who considered a heterogeneous triopoly game with an isoelastic demand function. Here, four different types of players and potentially different marginal costs are considered. Moreover, the assumption of an isoelastic demand function increases the nonlinearity of the final four-dimensional map. The stability of the resulting discrete-time dynamical system is analyzed. The existence of Neimark–Sacker bifurcation near the Nash equilibrium point of the game is shown. Also, based on the Kuznetsov’s normal form technique for discrete-time system, the stability of the Neimark–Sacker bifurcation is also discussed which indicates that the bifurcation is supercritical. Moreover, it is shown that the Nash equilibrium point of the game undergoes period-doubling (flip) bifurcation. Furthermore, the double route to chaotic dynamics in this model, via flip bifurcations and via Neimark–Sacker bifurcation of the Nash equilibrium point, is illustrated. Coexistence of multi-chaotic attractors of the model is illustrated. Simulation tools like bifurcation diagrams, stability regions of parameters, Lyapunov exponent spectrum, phase plots and basins of attraction are used to verify the complex dynamics of the game.     

Analysis of flow behavior and fluid forces in large cylinder bundles by numerical simulations

This paper presents a numerical investigation of the three-dimensional flow around an in-line cylinder arrangement with up to twenty-five cylinders under confinement, with a subcritical Reynolds number, in the context of flow-induced vibrations. Flow characteristics and patterns, as well as the force coefficients of the cylinders and Strouhal numbers were evaluated numerically with the large eddy simulation approach and validated against previously published experimental data. Two values for both the transversal (T/D = 1.5 and 3) and longitudinal (L/D = 2 and 4) spacing ratios were considered and combined to generate four different arrangements. The velocity distributions obtained in the simulations were in good agreement with the experimental data. Fluctuations in the force coefficients were characterized for each arrangement and found to be directly proportional to the turbulence kinetic energy upstream of each cylinder. Depending on the flow pattern, certain rows are subjected to greater flow force fluctuations. The dominant frequency, expressed by the Strouhal number, was also mapped throughout the arrangements and its distribution was characterized according to the observed flow patterns. Although the spacing ratios have a combined effect, their separate influence on the general behavior and distribution of fluid forces could be identified, as these are linked to the flow regimes. This knowledge allowed for the contribution to an already existing in-line tube bundle classification, which is useful in the diagnosis of flow-induced vibrations and the design of heat exchangers and other industrial equipment.     

Origins of group coordination: nonlinear dynamics and the role of verbalization

Coordination occurs when two or more people do the same or complimentary tasks simultaneously; its explanation game theory, nonlinear dynamics, and implicit learning theory. In the experiment, 12 four-person groups were allowed to discuss the coordination (card game) task while performing it; 12 other groups worked nonverbally. One to three group members were replaced during the game. Split-plot ANOVA showed that verbalizing groups performed better than nonverbalizing groups overall and showed more acute coordination learning curves, but verbalization did not compensate for the replacement of personnel. Groups that changed one or two players showed positive coordination transfer, but groups that changed three players did not. Nonlinear regression for temporal dynamics within verbalizing and nonverbalizing groups showed asymptotic stability for initial coordination learning and transfer to a difficult rule, a chaotic function when replacements were introduced, and asymptotic stability again when the team with replacements switched to the difficult rule.     

POD-based surrogate modeling of transitional flows using an adaptive sampling in Gaussian process

A surrogate model, based on proper orthogonal decomposition (POD) with the adaptive sampling method, was proposed to predict the transitional flow past rough flat plates simulated by a four-equation k-ω-γ-A_r transition model. Gaussian process regression was used to map the input parameters to the POD expansion coefficients. The variance and gradient of Gaussian process were taken as the criteria for the adaptive sampling. The proposed methodology was applied to a one-dimensional heat conduction problem and two-dimensional transitional flow past rough flat plates. At the same time, the results were compared with those of Halton sequences. With the same sample size, the adaptive method achieved a higher accuracy on the test set, and the proposed adaptive criterion could serve as an indicator for the model discrepancies.     

Fracture Mechanics of Corrosion Cracking in Concrete by Acoustic Emission

Nucleation of microcracks can be detected and analyzed by acoustic emission (AE), by which crack kinematics of locations, types and rientations are quantitatively estimated. The procedure was applied to clarify mechanisms of corrosion cracking. Based on fracture mechanics, numerical analysis was conducted by the boundary element method (BEM). Relations between the stress intensity factors and crack types were investigated by BEM solutions. In experiments, four types of crack patterns were nucleated by employing expansive agent. Following the surface crack, the diagonal crack and/or the horizontal crack propagated. The internal crack extended after the surface crack was terminated. Depending on the crack types, contributions of mode-I and mode-II were varied. According to AE results, four crack patterns observed differently consisted of tensile, mixed-mode and shear cracks. It is demonstrated that mechanisms of corrosion cracking in concrete are dominantly of mode-I failure along with a minor contribution of mixed-mode and mode-II.     

Finite element analysis of the fatigue crack growth rate in transformation toughening ceramics

The fatigue crack growth rate in the zirconia tetragonal polycrystal is analyzed through the finite element method. In order to achieve this purpose, a continuum based constitutive law for materials subjected to phase transformations has been suitably implemented into a commercial finite element code. The fatigue crack growth in a notched beam, subjected to a cyclic four points bending load, has been investigated through a sensitivity analyses with respect to the two most relevant constitutive parameters: one accounting for the amount of the transformation strain and one accounting for the activation energy threshold. The fatigue crack growth rate typical of transforming materials is characterized by two distinct stages: at the beginning of the crack propagation process, the crack growth rate exhibits a negative dependency on the applied stress intensity factor; thereafter, a linear positive dependency is observed. This two stage process is well caught by the finite element model presented in this paper. Moreover, the response of the computational analyses has shown that the strength of the transformation process is determinant for the crack growth process to be arrested.     

一种改进的自适应卡尔曼滤波及在组合导航中的应用

总结了常用的自适应滤波的方法,并提出一种新的自适应卡尔曼滤波技术,它克服了传统滤波器的不稳定问题,因为传统的卡尔曼滤波过程依赖于系统过程和测量过程的数学模型和其统计模型的正确性的滤波技术.自适应过程是利用测量新息序列和状态修正序列在估计移动窗内是分段静态,来直接估计系统噪声协方差Q和测量噪声协方差(R).仿真结果表明此方法可以提高GPS/INS组合导航系统的精度和可靠性.     

Preferred design of recurrent neural network architecture using a multiobjective evolutionary algorithm with un-supervised information recruitment: a paradigm for modeling shape memory alloy actuators

Shape memory alloys (SMAs) are able to compensate any undergoing plastic deformations and return to their memorized shape. Such a behavior persuades industrialists to use them for different engineering applications, as smart actuators and sensors. Because of their vast applications, it is crucial to engineers to develop effective identification tools capable of simulating the behavior of SMAs. However, SMA actuators have complex and hysteric behavior that in turn obstructs the modeling process. The motivation behind the current study emanates in the pursuit of developing efficient prediction tools for effective modeling of SMA actuators. Actually, after several experiments and software simulations, the authors develop a hybrid intelligent tool which takes advantage of the self-organizing Pareto based evolutionary algorithm (SOPEA) and simultaneous recurrent neural network (SRNN), as a black-box model, to automatically identify the behavior of SMA. SOPEA is a multiobjective evolutionary algorithm which is based on the concepts of survival of the fittest, non-dominated sorting and information recruitment. The information recruitment is guaranteed by applying an un-supervised neuro computing technique, i.e. adaptive self organizing map (ASOM) with conscience mechanism. ASOM is an un-supervised network that assists SOPEA to recognize the non-dominated patterns and produce further non-dominated solutions. Together with the structure of SOPEA, the authors follow a comprehensive preference-based strategy to exploit the desired regions in the Pareto front. This occurs through introducing deliberate reference points. The outcome method is applied to the design of SRNN for modeling the SMA actuator. It is demonstrated that the designed optimization tool can show acceptable performance for the present case study within the imposed computational budget. Besides, through a rigorous experimental procedure, it is indicated that by applying an efficient artificial system, the behavior of SMA can be identified without any specific knowledge of the physical conditions and governing equations.     

Discrete non-linear adaptive data driven control based upon simultaneous perturbation stochastic approximation

A novel adaptive data driven control strategy is proposed for general discrete non-linear systems. The controller is designed based upon the Simultaneous Perturbation Stochastic Approximation (SPSA) method, and is constructed through use of a Function Approximator (FA), which is fixed as a neural network here. In this novel control strategy, the parametric estimation is designed to be adaptive with convergence analysis, and the control ability has been greatly improved. The proposed control method is finally applied into the non-linear tracking problems, as well as near-optimal control problems for discrete-time non-linear systems. Simulation comparison tests were conducted on typical non-linear plants, through which, the convergence and feasibility of the proposed adaptive data driven control strategy are well demonstrated.     

Experimental Investigation of Fracture Process Zone in Rocks Damaged Under Cyclic Loadings

Compared with other materials, most rocks generally fail in a brittle fashion rather than exhibiting yielding or purely plastic deformation. However, the initiation and coalescence of micro-cracks in the nonlinear region, known as the ‘fracture process zone’ (FPZ), are the primary reason for fracture propagation in rocks. Different elasticity-related models proposed for determining the features of the FPZ have not achieved an adequate understanding of its various fracture patterns. Based on previous experiments and numerical models, micro-crack density has been shown to be a function of loading history and to vary depending on whether the loading is monotonic or cyclic. The aim of the study reported here was to examine the different patterns of the FPZ under various types of cyclic loading and to quantitatively define damage and fracture patterns through the grains or rock matrix. Considerable laboratory testing was conducted, and fractured samples were investigated by computerised tomography scanning, supported by thin-section analysis. In the study, two different types of cyclic loading were tested: stepped and continuous. A diametral compressive loading was applied at predetermined amplitude and frequency with the continuous cyclic loading. The applied cyclic diametral compressive load was returned to the original level after each step, and at the next step, the amplitude started from zero, with stepped cyclic loading (SCL). An average 30 % strength reduction was found due to the SCL and emergence of high micro-fracture density in the FPZ. We presume that hard rock breakage techniques will be improved, especially for rock-cutting technologies, such as drag bits and oscillating disc cutting, by understanding the effects of cyclic loading on rock strength.