Seeking Strategy Research Articles

Source Seeking With a Nonholonomic Vehicle in Static and Dynamic Spatial Fields

ABSTRACTIn this paper, a novel source seeking strategy is presented. A single autonomous vehicle is modeled as a kinematic unicycle moving in two‐dimensional space within a spatial field. The proposed control scheme allows the vehicle to reach a neighborhood of the source of the spatial field in finite time. In this work, the spatial field can be static, translating or dynamically evolving. The control strategy, based on the definition of a reference trajectory and on a second order sliding mode extremum seeking approach, exploits only a point measurement at the vehicle position, and does not require knowledge or an estimate of the spatial gradient of the phenomenon of interest. Explicit bounds on the reference trajectory parameters are introduced in order to guarantee finite time convergence to a neighborhood of the source. The approach is tested in simulation on static and dynamic spatial fields.

Distributed generalized Nash equilibrium seeking strategy design for multi‐cluster games of high‐order players

AbstractIn this paper, a multi‐cluster game (MCG) of autonomous players is explored. Different from the existing MCGs, the high‐order dynamics of players is taken into account in our problem. Owing to the high‐order dynamics of players, existing strategies for MCGs are unable to tackle our problem. For purpose of seeking the variational generalized Nash equilibrium (vGNE) of the game, a distributed strategy is designed on the basis of gradient descent and state feedback, in which a distributed estimator is embedded for the players to estimate the decisions of other players. Furthermore, the asymptotical convergence of the strategy is analyzed via Lyapunov stability theory and variational analysis. Finally, the effectiveness of our method is verified through a numerical simulation.

Distributed NE and GNE seeking for heterogeneous multi-player games over directed communication networks.

The non-cooperation game with heterogeneous dynamics is of both theoretical significance and practical relevance because of its extensive penetration into various fields, such as the game confrontation composed of unmanned aerial vehicles and unmanned vehicles or the power generation systems with varied turbine assemblies. To solve such a game problem, this paper investigates distributed Nash equilibrium (NE) and generalized Nash equilibrium (GNE) seeking problems for heterogeneous multi-player systems in non-cooperation games. First, by incorporating the output regulation technique, a distributed NE seeking strategy is designed for heterogeneous multi-player games over undirected communication networks. Then, the GNE seeking problem subject to coupling constraints among multiple players is further studied and a distributed GNE seeking strategy is developed by utilizing the Lagrange multiplier and the output regulation technique. Second, in the case of directed communication networks, both distributed NE and GNE seeking strategies are proposed by employing new type of auxiliary variables to compensate for the unbalanced networks. Compared with some existing results on distributed NE and GNE seeking strategies, both the dynamics of players and communication networks are extended further. Finally, numerical simulations are presented to show the effectiveness of the NE and GNE seeking strategies.

Active sampling as an information seeking strategy in primate vocal interactions

Active sensing is a behavioral strategy for exploring the environment. In this study, we show that contact vocal behaviors can be an active sensing mechanism that uses sampling to gain information about the social environment, in particular, the vocal behavior of others. With a focus on the real-time vocal interactions of marmoset monkeys, we contrast active sampling to a vocal accommodation framework in which vocalizations are adjusted simply to maximize responses. We conduct simulations of a vocal accommodation and an active sampling policy and compare them with actual vocal interaction data. Our findings support active sampling as the best model for real-time marmoset monkey vocal exchanges. In some cases, the active sampling model was even able to partially predict the distribution of vocal durations for individuals to approximate the optimal call duration. These results suggest a non-traditional function for primate vocal interactions in which they are used by animals to seek information about their social environments.

Alternative Alpha Seeking Strategy with EVA Long‐Short: Evidence from the Korean Stock Market*

AbstractEconomic value added (EVA) is a useful concept for creating investment strategies for fund managers and scholars. This paper analyzes an alpha‐seeking strategy with EVA. We use a long‐short portfolio with high EVA and low EVA stocks. Using the normalized EVA, we construct a portfolio from the first to the fifth quintile and test the effectiveness of the strategy with the Carhart four‐factor model. We find the following: (1) The portfolios with high EVA stocks outperform those with low ones; (2) EVA‐based long‐short portfolio generates 6.5% return per annum. This paper provides an empirical basis for launching a new equity fund with EVA in Korea. This strategy suggestion could also be extended to introduce new EVA investment strategies in other global markets.

Editorial Introduction to Issue 39: Managing Complexity and Knowledge in Enterprise Projects

This issue of CSIMQ includes five articles selected on the topics of complexity management and knowledge management in enterprises from various perspectives and towards diverse goals: the economic and societal perspective seeking strategy fulfillment with the help of enterprise architecture management, the operational performance perspective, which requires grounding management decisions on data insights, and the human aspect perspective to facilitate collaboration, creativity and innovation. Methodologically, the issue reports a mix of conceptual modeling and analytics approaches, suggesting an emerging requirement to balance or alternate, in complexity management, abstraction-based analysis, and data-oriented analytics.

Distributed Nash equilibrium seeking for multi‐agent systems with uncertainty in the cost function

AbstractIn this paper, the Nash equilibrium (NE) seeking problem is investigated for a class of ‐integrator multi‐agent system with uncertain parameter in the cost function. In the game setup, each agent only accesses its neighbors' information. Without knowing the probability distribution of the uncertain parameter, the robust counterpart of the studied game is considered. Due to the nonsmoothness of the robust game, a smooth game that consists of real agents as well as fictive agents dealing with uncertainty is formulated. In contrast to conventional robust convex‐concave games, the assumption on the uncertain parameter is relaxed to Polyak‐Łojasiewicz (PL) inequality. Based on the relationship between the robust game and its reformulated version, a distributed NE seeking strategy is developed such that the states of the non‐cooperative agent can converge to the NE solution. At the end, numerical examples are given to verify the validity of the proposed method.

Attack-Resilient Distributed Nash Equilibrium Seeking of Uncertain Multiagent Systems Over Unreliable Communication Networks.

This article investigates the distributed Nash equilibrium (NE) seeking problem of uncertain multiagent systems in unreliable communication networks. In this problem, the action of each agent is subject to a class of nonlinear systems with uncertain dynamics, and the communication network among agents will be affected by the nonperiodic denial of service (DoS) attacks. Note that, in this insecure network environment, the existence of DoS attacks will directly destroy the connectivity of the network, which leads to performance degradation or even failure of the most existing distributed NE seeking algorithms. To address this problem, we propose a two-stage distributed NE seeking strategy, including the attack-resilient distributed NE estimator and the neuroadaptive tracking controller. The estimator based on the projection subgradient method and the consensus protocol can converge exponentially to virtual NE against DoS attacks. Then, the neuroadaptive tracking controller is designed for uncertain multiagent systems with the output of the estimator as the reference signal such that the actual action of all agents can reach NE. Based on the Lyapunov stability theory and improved average dwell time automaton, the stability of the estimator and the controller is proven, and all signals in the closed-loop system are uniformly bounded. Numerical examples are presented to verify the effectiveness of the proposed strategy.

Students’ Strategies to Overcome Public Speaking Anxiety

Public speaking anxiety (PSA) is a problem that often occurs in the language learning process therefore this study was conducted to find the strategies students use to overcome the public speaking anxiety they experience using the theory developed by Kondo and Ying Ling (2004). This study used a quantitative method with a descriptive approach. The participants of this research were 40 students of the English education study program of FKIP at Universitas Tanjungpura. The results showed that relaxation strategy is the most chosen strategy by students as the strategy they use to overcome their public speaking anxiety with the percentage 83.2%, followed by the preparation strategy as the second strategy with the percentage 80.1%, then third is peer seeking strategy chosen by 80% students and the last is the positive thinking strategy as much as 78.2%. The limitations of this study are as follows: it does not provide data on students' levels of anxiety, lacks diversity in the tools used, focuses solely on students who have completed the course, and does not explore strategies beyond those suggested in the questionnaire.

Distributed Nash Equilibrium Seeking Strategies Under Quantized Communication

This paper is concerned with distributed Nash equilibrium seeking strategies under quantized communication. In the proposed seeking strategy, a projection operator is synthesized with a gradient search method to achieve the optimization of players' objective functions while restricting their actions within required non-empty, convex and compact domains. In addition, a leader-following consensus protocol, in which quantized information flows are utilized, is employed for information sharing among players. More specifically, logarithmic quantizers and uniform quantizers are investigated under both undirected and connected communication graphs and strongly connected digraphs, respectively. Through Lyapunov stability analysis, it is shown that players' actions can be steered to a neighborhood of the Nash equilibrium with logarithmic and uniform quantizers, and the quantified convergence error depends on the parameter of the quantizer for both undirected and directed cases. A numerical example is given to verify the theoretical results.

THE INFLUENCE OF PERPETRATOR IDENTITY ON ADOLESCENT SCHOOLGIRLS’ SEXUAL HARASSMENT COPING STRATEGIES IN MBULU TOWN COUNCIL, MANYARA REGION

The widespread reports of school adolescents being victimized by sexual harassment have raised concerns towards understanding how adolescents cope with such incidents. This study assessed the influence of perpetrator identity on the likelihood of schoolgirls employing certain sexual harassment coping strategies. A cross-sectional descriptive survey design was utilized in this study. The target population constituted of adolescent ordinary level secondary schoolgirls in Mbulu Town Council and the sample size was 400 girls. The sampling procedure was a two stages cluster sampling. The data were collected using a questionnaire and analyzed by binary logistic regression using the statistical package for social science software (SPSS). Perpetrator identities were found to influence coping strategies adopted by schoolgirls. Senior students revealed an association with normalization coping strategy while strangers were associated with engagement coping strategy. Classmates, teachers, senior students and strangers were associated with detachment coping strategy, whereas non-teaching staff was associated with help-seeking coping strategy. It is recommended that adolescents should be provided with sexuality education so as to mitigate the tendency of normalizing harassment in peer relationships. Also, further interventions should focus on emphasizing the usage of help seeking strategy rather than detachment. Moreover, boarding schools could be a potential solution for preventing encounters with strangers to and from school.

Distributed GNE Seeking Strategy for Second-Integrator Multiplayer Systems Over Directed Topologies.

This article studies the generalized Nash equilibrium (GNE) seeking problem of second-integrator multiplayer systems. In particular, each player is endowed with an individual payoff function with respect to collective decision variables, and simultaneously, a coupling inequality constraint and a set constraint are imposed to each player. The players communicate with their local neighbors over a directed topology. To begin with, a distributed-observer-based seeking strategy is synthesized by leveraging a proper composite variable. It is first demonstrated using nonsmooth analysis that the established distributed observer enables each player to accurately estimate the decision variables of others in terms of a strongly connected topology condition. Upon this basis, all the decision variables are then shown to converge to the expected GNE asymptotically borrowing from convex theory. In addition, three extension results are also given under the built GNE seeking framework. First, under the postulation that the velocity information is unavailable, a velocity-free distributed GNE seeking strategy is synthesized for second-integrator systems by implementing a proper auxiliary dynamics. Second, we consider nonlinear Euler-Lagrange systems with unknown inertia parameters and synthesize an improved distributed GNE seeking strategy resorting to an adaptation technique. Third, we focus on integrator chain systems and synthesize a modified distributed GNE seeking strategy using a new composite variable based on a proper coordinate transformation. For three extension cases, we all show in detail the achievement of the GNE seeking objective. Finally, a practical example is simulated to confirm the built GNE seeking results.

Ethanol regulation in yeast fed-batch cultures by stabilizing extremum seeking

In this study, an original model-free stabilizing extremum seeking (STAB-ESC) strategy is applied to optimize yeast fed-batch culture productivity. To this end, the ethanol concentration is tracked at a low level, to approach the yeast growth optimal conditions. Overflow metabolism effects, resulting from the cell's limited respiratory capacity, are considered using a macroscopic model with discontinuous kinetics. The detrimental impact of input saturation on the proposed STAB-ESC stability is overcome using a state-dependent switching control strategy. The resulting methodology is illustrated with numerical results where the robustness of the controller to measurement noise is also highlighted.

Prescribed-Time Fully Distributed Nash Equilibrium Seeking Strategy in Networked Games

Prescribed-Time Fully Distributed Nash Equilibrium Seeking Strategy in Networked Games

Adaptive IIF Seeking Strategy for Virtual Impedance Stabilization to Stabilize Cascaded Systems with Background Harmonics

Adaptive IIF Seeking Strategy for Virtual Impedance Stabilization to Stabilize Cascaded Systems with Background Harmonics

Fixed-Time Consensus-Based Event-Triggered Nash Equilibrium Seeking Strategy

Fixed-Time Consensus-Based Event-Triggered Nash Equilibrium Seeking Strategy

The Lévy flight foraging hypothesis: comparison between stationary distributions and anomalous diffusion *

We consider a stationary prey in a given region of space and we aim at detecting optimal foraging strategies. On the one hand, when the prey is uniformly distributed, the best possible strategy for the forager is to be stationary and uniformly distributed in the same region. On the other hand, in several biological settings, foragers cannot be completely stationary, therefore we investigate the best seeking strategy for Lévy foragers in terms of the corresponding Lévy exponent. In this case, we show that the best strategy depends on the region size in which the prey is located: large regions exhibit optimal seeking strategies close to Gaussian random walks, while small regions favor Lévy foragers with small fractional exponent. We also consider optimal strategies in view of the Fourier transform of the distribution of a stationary prey. When this distribution is supported in a suitable volume, then the foraging efficiency functional is monotone increasing with respect to the Lévy exponent and accordingly the optimal strategy is given by the Gaussian dispersal. If instead the Fourier transform of the distribution of a stationary prey is supported in the complement of a suitable volume, then the foraging efficiency functional is monotone decreasing with respect to the Lévy exponent and therefore the optimal strategy is given by a null fractional exponent (which in turn corresponds, from a biological standpoint, to a strategy of ‘ambush’ type). We will devote a rigorous quantitative analysis also to emphasize some specific differences between the one-dimensional and the higher-dimensional cases.

Distributed least-distance formation control for Euler–Lagrange systems: A game-based approach

This paper presents a distributed algorithm to achieve least-distance formation control for Euler–Lagrange systems, which is crucial for practical applications such as enemy capturing, island defensing and escorting, to name just a few. Compared with most of existing works on formation control, not only the formation of the desired shape but also the optimization of a global distance function needs to be achieved for Euler–Lagrange systems. By introducing a game-based formulation, the least-distance formation control problem is transferred to a least-norm Nash equilibrium seeking problem. A distributed Nash equilibrium seeking strategy is proposed by incorporating adaptive control laws with regularization-based optimization algorithms. The adaptive control laws are leveraged to accommodate unknown parameters for Euler–Lagrange systems. Moreover, the regularization-based optimization algorithms are employed to achieve formation and distance optimization simultaneously. It is found that the proposed algorithm can globally asymptotically steer agents’ states to the least-norm Nash equilibrium, thus achieving distributed least-distance formation control for Euler–Lagrange systems. Finally, we show the effectiveness of the algorithms by conducting simulation studies for a network of quadrotors.

Seeking strategy design for distributed nonsmooth games and its application

This paper investigates the nonsmooth noncooperative games (NGs) over unbalanced digraphs, where each player has a nondifferentiable payoff function. Meanwhile, these players are subject to local nonsmooth inequality constraints, local convex set constraints and coupled equality constraints. Due to the coexistence of nonsmooth payoff functions, unbalanced digraphs and constraints, existing generalized Nash equilibrium (GNE) seeking strategies are fail to address our problem. Based on subgradient descents, differential inclusions, projection and primal-dual methods, we develop a distributed seeking strategy. Besides, the convergence of the strategy is proved. Finally, the proposed method is applied to electricity market games (EMGs) of smart grids.

Fully Distributed Nash Equilibrium Seeking for High-Order Players With Actuator Limitations

This paper explores the problem of distributed Nash equilibrium seeking in games, where players have limited knowledge on other players' actions. In particular, the involved players are considered to be high-order integrators with their control inputs constrained within a pre-specified region. A linear transformation for players' dynamics is firstly utilized to facilitate the design of bounded control inputs incorporating multiple saturation functions. By introducing consensus protocols with adaptive and time-varying gains, the unknown actions for players are distributively estimated. Then, a fully distributed Nash equilibrium seeking strategy is exploited, showcasing its remarkable properties: 1) ensuring the boundedness of control inputs; 2) avoiding any global information/parameters; and 3) allowing the graph to be directed. Based on Lyapunov stability analysis, it is theoretically proved that the proposed distributed control strategy can lead all the players' actions to the Nash equilibrium. Finally, an illustrative example is given to validate effectiveness of the proposed method.