Non-cooperative Strategies Research Articles

Compatibility of Leadership Styles with Cooperative and Non-Cooperative Conflict Management Strategies

Conflict among leaders and subordinates is natural meanwhile same is observed among headteachers and teachers; if it is not managed appropriately can create an adverse impact on organizational climate and subsequently on performance. A plethora of literature looked at the leadership styles that have direct/indirect influence on cooperative and non-cooperative conflict management practices. The present study examines the compatibility between leadership styles and cooperative and non-cooperative conflict management strategies of the secondary schools in Punjab. 360 randomly selected head teachers participated in this study. Two questionnaires were used, one for leadership styles and the other for cooperative and non-cooperative conflict management strategies. The results indicated that cooperative strategies of conflict management such as accommodation, collaboration and compromising are much helpful in a place where democratic leadership style was being practised, and authoritative leaders intended to follow non-cooperative such as competing and avoiding strategies in order to manage conflicts in schools. Therefore, it can be inferred that Headteachers who perceived to exhibit a more democratic style of leadership adopted cooperative strategies of conflict management. The headteachers who were perceived to exhibit a more autocratic leadership style opted for non-cooperative strategies of conflict management.

Some numerical results for control of 3D heat equations using Nash equilibrium

This article deals with some numerical strategies to solve control problems for heat equations with Dirichlet boundary conditions. We assume that we can act on the system through two controls. We use a non-cooperative bi-objective optimization strategy, to which we define the associated Nash equilibrium. More precisely, for such problems, we look for Nash equilibrium associated with optimal cost functionalities, which correspond to appropriate non-cooperative strategies. To numerically calculate the solutions, we combine finite difference methods in time and finite element methods in space. In each system presented, we seek to solve the discretized problems using three iterative methods: Fixed Point, Gradient with Fixed Step, and Conjugated Gradient, and the developed algorithms will be analyzed and compared. The data programming and computational simulations are performed in the software FreeFem ++ and Matlab.

Non-cooperative strategy for negative self-expression of a pessimistic communicant

Non-cooperative strategy for negative self-expression of a pessimistic communicant

The vertical cooperation and pricing strategies of electric vehicle supply chain under brand competition

This paper considers an electric vehicle supply chain composed of a battery supplier, a well-known brand manufacturer (Manufacturer A) and an ordinary brand manufacturer (Manufacturer B). Three strategies are studied, namely, the noncooperative strategy (hereafter “Strategy N”), the cooperation strategy between the battery supplier and Manufacturer A (hereafter “Strategy S-A”), and the cooperation strategy between the battery supplier and Manufacturer B (hereafter “Strategy S-B”). Under these strategies, we investigate the optimal sales prices of the battery and electric vehicles of the two brands. We then analyze the impacts of brand effect on the demands of the two electric vehicles and the profits of all enterprises. The theoretical and numerical analyses present some valuable findings. First, Strategy S-A improves the demand and the profit of Manufacturer A, but reduces the demand and the profit of Manufacturer B; inversely, Strategy S-B increases the demand and profit of Manufacturer B, but decreases the demand and profit of Manufacturer A. Under Strategy S-B, the total demand for the two brands of electric vehicles is the largest. Second, Strategy S-A can intensify price competition, while Strategy S-B can weaken price competition between the two manufacturers. Third, when the degree of brand difference is relatively low, or the ratio of Manufacturer A’s bargaining power to Manufacturer B’s bargaining power is high, the battery supplier’s profit under Strategy S-B is the highest; otherwise, the battery supplier can obtain the highest profit from Strategy S-A. Finally, vertical cooperation strategies do not always improve the overall profitability of the supply chain.

Game-theoretic analyses of strategic pricing decision problems in supply chains

We consider strategic pricing problems in which each firm chooses between a non-cooperative (individual pricing) strategy and a cooperative (price negotiation) strategy. We first analyze a monopoly supply chain involving a supplier and a retailer, and then investigate two competing supply chains each consisting of a supplier and a retailer. We find that an appropriate power allocation between the supplier and the retailer can make the two firms benefit from negotiating the wholesale and retail prices. When the supplier negotiates the wholesale price, the retailer’s cooperative strategy can always induce supply chain coordination in the monopoly setting, whereas the two supply chains in the duopoly setting can be possibly coordinated only when the retailers determine their retail prices individually. In both the monopoly and duopoly settings, the wholesale price negotiation is a necessary part of the communications between supply chain members. When the supply chain competition intensifies, all firms are more likely to determine their prices individually rather than to negotiate their prices.

Jamming-Assisted Legitimate Eavesdropping and Secure Communication in Multicarrier Interference Networks

This article investigates legitimate eavesdropping and secure communication in a multicarrier interference network, where a suspicious link coexists with an unsuspicious link, in the presence of a full-duplex monitor. It is assumed that the unsuspicious users (UUs) are under illegal eavesdropping threat from the suspicious users (SUs), and the monitor can send jamming signals to interfere with the SUs. The UUs are required to cooperate with the monitor for reducing the secrecy outage probability of the UUs to be lower than that without the monitor’s jamming. Under this secrecy outage constraint along with the transmit power constraints, the problem for maximizing the successful eavesdropping probability of the monitor by jointly allocating the transmit powers of the monitor and the UUs is investigated. The problem is solved with the Lagrange duality method by proving the time-sharing property holds, where two algorithms are proposed for obtaining the dual function based on the block coordinate descent method and the successive convex approximation method. Simulation results verify that the proposed algorithms are superior to the noncooperative strategy and the passive eavesdropping strategy, and achieve high successful eavesdropping probability and low secrecy outage probability simultaneously.

Eye Gaze Patterns of Decision Process in Prosocial Behavior.

Understanding human behavior remains a grand challenge across disciplines. We used eye tracking to investigate how visual perception is associated with a strategic behavior in the decision process. Gaze activity and eye movement patterns were measured in 14 human participants with different decision strategies. We also employed a social domain to force strategic behavior. We find that social interaction significantly improves the level of cooperation, prosocial decisions, and overall cooperative strategy in experiment participants. Gaze behavior in individuals with a cooperative strategy is characterized by a greater number of fixations and frequent gaze returns to the scanned areas. On the contrary, individuals with a non-cooperative strategy approach decision-making task stimuli in a distinct way with long-duration fixations and a low number of gaze returns to the areas already scanned. Social domain, which enhances cooperation and prosocial behavior, makes participants more attentive to the task stimuli in our experiments. Moreover, prolonged gaze at the area of cooperative choice testifies in favor of the cooperative decision.

On the computation of Nash and Pareto equilibria for some bi-objective control problems for the wave equation

This paper deals with the numerical implementation of a systematic method for solving bi-objective optimal control problems for wave equations. More precisely, we look for Nash and Pareto equilibria which respectively correspond to appropriate noncooperative and cooperative strategies in multi-objective optimal control. The numerical methods described here consist of a combination of the following: finite element techniques for space approximation; finite difference schemes for time discretization; gradient algorithms for the solution of the discrete control problems. The efficiency of the computational methods is illustrated by the results of some numerical experiments.

A Cooperative Computing Strategy for Blockchain-Secured Fog Computing

Fog computing is an emerging paradigm in provisioning computing and storage resources for the Internet-of-Things (IoT) devices. In a fog computing system, all devices can offload their data or computationally intensive tasks to nearby fog nodes, instead of to the distant cloud. As compared with cloud computing, fog computing can significantly reduce the transmission delay between IoT devices and computing servers. However, the current fog system is rather susceptible to malicious attacks. To increase the security level, we propose to partition the fog system into fog node clusters (FNCs), with fog nodes (FNs) in one cluster sharing the same access control list (ACL) which is protected by a blockchain. Generating blockchains requires tremendous computing power and can rapidly drain the computing capacities of FNs. In this article, we first customize the blockchain for FNC to reduce the required computing power consumption and storage spaces. Second, a new scheme is designed for the blockchain-based FNC (BFNC) to recover ACL automatically. In addition, we propose a heuristic algorithm to reduce the time to acquire hash values of blocks by computing cooperatively with all available devices. The simulation results have demonstrated that using the cooperative computing strategy can reduce the time of computing a block hash than noncooperative strategies.

The Formation Mechanism of Green Dairy Industry Chain from the Perspective of Green Sustainable Development

By constructing an evolutionary game model of green dairy industry chain from the perspective of green sustainable development, this paper analyzed the evolution process of strategy selection of dairy farmers and dairy enterprises under the supervision of the government. The study found the following. (1) In the absence of supervision, even if the initial cooperation willingness of dairy farmers and dairy enterprises is strong, once the additional cost of their input of “green production” is less than the additional benefit, they will eventually choose noncooperative strategy. (2) In the case of government supervision, when the government punishment or subsidy is not strong enough, the strategic choice of dairy farmers and dairy enterprises will fluctuate repeatedly, and the game equilibrium cannot be reached. However, when the government punishments and subsidies are strong enough, dairy farmers and dairy enterprises will choose to cooperate in their own interests. At this time, government subsidies have a greater impact on the evolution of bilateral cooperation than government punishments. (3) The reduction of green production cost can promote the formation of the green dairy industry chain, which is conducive to the green dairy industry chain system to achieve an ideal equilibrium state.

Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning

The problem of learning simultaneously several related tasks has received considerable attention in several domains, especially in machine learning with the so-called multitask learning problem or learning to learn problem [1], [2]. Multitask learning is an approach to inductive transfer learning (using what is learned for one problem to assist in another problem) and helps improve generalization performance relative to learning each task separately by using the domain information contained in the training signals of related tasks as an inductive bias. Several strategies have been derived within this community under the assumption that all data are available beforehand at a fusion center. However, recent years have witnessed an increasing ability to collect data in a distributed and streaming manner. This requires the design of new strategies for learning jointly multiple tasks from streaming data over distributed (or networked) systems. This article provides an overview of multitask strategies for learning and adaptation over networks. The working hypothesis for these strategies is that agents are allowed to cooperate with each other in order to learn distinct, though related tasks. The article shows how cooperation steers the network limiting point and how different cooperation rules allow to promote different task relatedness models. It also explains how and when cooperation over multitask networks outperforms non-cooperative strategies.

Evolutionary Game Analysis of Tripartite Cooperation Strategy under Mixed Development Environment of Cascade Hydropower Stations

Joint operation of cascade hydropower stations maximizes the utilization rate of water resources of a river basin and the benefit of the entire river system. However, under mixed development environment of cascade hydropower stations, i.e. simultaneous existence of operating and under-construction hydropower stations, the difficulty of the joint operation is increased. Moreover, this difficulty is further enhanced due to the cooperation among multiple stakeholders and uncertain evolutionary characteristic of stakeholder’s strategy. To handle these problems, this paper takes two upstream operating hydropower stations and one downstream hydropower station under construction as research objects, where one of upstream hydropower station locates in a tributary. First, all possible strategy combinations among these three stakeholders are comprehensively analyzed, and the benefit of each stakeholder strategy under each strategy combination is respectively calculated. A tripartite evolutionary game model is then established. It aims at exploring directions and conditions of cooperative and non-cooperative strategies evolving into stable states. Finally, the exploration results find that the strategy evolution of a stakeholder relies on its partners’ behaviors and net benefit of self-behavior; the tripartite cooperation will eventually form four stable states; the conditions for cooperation between upstream and downstream hydropower stations are that the compensation paid by downstream hydropower station is greater than the loss of upstream power generation and downstream project benefit is greater than the sum of compensation expenditure and risk benefit.

The Existence of Consensus Equilibria for Data Trading under the Framework of Internet of Things (IoT) with Blockchain Ecosystems

Abstract The goal of this paper is to use a new notion called “Consensus Game (CG)” with motivation from the mechanism design of blockchain economy under the consensus incentives from Bitcoin ecosystems in financial technology (Fintech) to study the existence of equilibria for the data trading under the framework of Internet of Things (IoT). By a fact that for a given sets of sensors, sensors may take action in cooperative, or noncooperative strategies (games), we formulate s model (called “Consensus Game of IoT”) to analyze this competitive situation among the sensors with the mixture of cooperative and noncooperative strategy (game). Then we provide the analytical condition for the existence of the consensus games of IoT in general. The application shows that the concept of consensus games of IoT may play a key role for the study of data trading under the framework of IoT associated with Blockchain ecosystems.

Joint optimal decisions on pricing and warranty policy of duopoly supply chain with one common retailer

Early researches related to the interaction between manufactures for complementary products, mainly considered price as only the dimension of competition. With the increasing competition in capturing the market share, manufactures cannot compete by only lowering prices. In this paper, we assume that besides the price, the manufactures choose warranty as the competitive strategy of two different but substitutable products in a duopoly supply chain with one common retailer. Furthermore, two cases are considered (i) only one manufacturer adopts warranty policy as a competitive strategy against the other, (ii) both manufacturers offer warranty on their product, to study under which situation offering a warranty becomes more profitable for a manufacturer while the other competitive manufacturer has already adopted warranty policy. The profit functions of the manufacturers and the retailer are then maximized under manufacturers' cooperative and non-cooperative strategies. We then compare the scenarios under different decision strategies numerically, which gives some insights on changes of key parameters to help the decision makers to capture the market.

ACOA-AFSA Fusion Dynamic Coded Cooperation Routing for Different Scale Multi-Hop Underwater Acoustic Sensor Networks

The limited energy supply of underwater nodes is one of the key issues for the multi-hop underwater acoustic sensor networks (UWA-SN). In this paper, the fusion scheme based on ant colony optimization algorithm (ACOA), artificial fish swarm algorithm (AFSA) and dynamic coded cooperation (DCC) strategy, named as ACOA-AFSA fusion DCC routing algorithm, has been proposed for routing in the multi-hop UWA-SN, aiming at simultaneously reducing the energy consumption and enhancing the robustness. In the proposed ACOA-AFSA fusion DCC routing algorithm, the randomness of the AFSA and the positive feedback mechanism of the ACOA enable the algorithm to find the global optimal routing more efficient and accurate. In addition, most existing routing protocols consider the large-scale networks (more than 100 nodes), while the medium- and small-scale networks (less than 100 nodes) are more practical in nowadays' multi-hop UWA-SN. The network scale affects the optimal design of routing protocols in terms of energy saving. Considering the practical situation, we compare the proposed scheme with other four existing artificial intelligence (AI) routing algorithms in the medium- and small- scale multi-hop UWA-SN, which is instructive for application of AI in practical multi-hop UWA-SN. The simulation results show that the proposed ACOA-AFSA fusion DCC routing algorithm can reduce the energy consumption by 40.1% compared to that with non-cooperative strategy in the multi-hop UWA-SN with 20 nodes. The proposed routing algorithm also consumes less energy than other four existing AI routing algorithms in the medium-scale multi-hop UWA-SN with 50 nodes or 100 nodes. However, for the small-scale case with 10 nodes, the advantage is not very obvious. In the meantime, the proposed ACOA-AFSA fusion DCC algorithm is compatible with the ACOA-AFSA fusion non-cooperative algorithm, and the complexity is acceptable, which is very appealing to the time-varying marine environments.

Non-Cooperative Distributed MPC with Iterative Learning

This paper presents a novel framework of distributed learning model predictive control (DLMPC) for multi-agent systems performing iterative tasks. The framework adopts a non-cooperative strategy in that each agent aims at optimizing its own objective. Local state and input trajectories from previous iterations are collected and used to recursively construct a time-varying safe set and terminal cost function. In this way, each subsystem is able to iteratively improve its control performance and ensure feasibility and stability in every iterations. No communication among subsystems is required during online control. Simulation on a benchmark example shows the efficacy of the proposed method.

Application of a Coordination Model for a Large Number of Stakeholders with a New Game Theory Model

Water allocation is an important issue for systems with multiple stakeholders. Individual and collective decisions are very important for such systems. Thus, a new integrated game model is proposed to create a good balance between cooperative and non-cooperative strategies. A dam-aquifer system was selected for the case study in Iraq. The system referred to should supply different stakeholders with water requirements. Three game models are used: 1) cooperative theory, non-cooperative theory, new integrated game structure. Effective factors in the way of cooperation was considered to demonstrate variations in the allocation of water to the stakeholders. The results of the cooperative or centralized model were considered as the best results. The results indicated that the new game model had good agreement with the centralized model. The outputs indicated that the allocation share of the downstream coalition could increase 4, 5 and 7% for high, medium and low inflow, respectively when the allocation share of the upstream coalition decreased 5%, 6% and 5% for high, medium and low inflow, respectively. The inflow excess volume at 90%, 50%, and 10% are considered as low inflow, medium inflow, and high inflow, respectively. It has been observed that the allocated volume of water to coalition downstream is increased by decreasing the more allocated volume of water to the coalition upstream. In addition, the new model supported the individual profits by applying the rationality decision while the cooperative game did not consider the individual benefits. In addition, the effect of inflows to reservoirs was considered to investigate the issue of water allocation in a critical condition.

A modified economic order quantity of vendor – buyer non-cooperative supply chain model for imperfect quantity and inspection error using the nash equilibrium concept

In this paper, the Economic Order Quantity (EOQ) of two-level supply-chain systems has been analyzed using the Nash Equilibrium concept. In this paper, a two-echelon supply chain consisting of a single vendor and a single buyer that both under the non-cooperative strategy. A mathematical analysis method, which according to appropriate literature, data and recent research result, is used to determine the mathematical formula of expected individual total cost both vendor and buyer, expected total cost of inventory system and also EOQ of decision variables. The non-cooperative strategy is used by the vendor and buyer to gain their optimal revenue. Thereby, game theoretical solution which is Nash equilibrium concept is used to determine the economic order quantity of this system. In this study, several assumptions are considered like the existence of the imperfect quality product in the manufacturing process and inspection error (Type I and Type II) in buyer’s place. To the best of authors’knowledge, this is the first paper that deals with a game theoretical solution, which is especially Nash equilibrium, in probabilistic supply chain under the imperfect condition and inspection error

The Tactics of Verbal Countermanipulation in Russian Political Video Blogs

The author of the article states that in spite of the fact that manipulation has been broadly studied in various areas of science, such as psychology, sociology, politology, linguistics, etc., countermanipulation (the response action to manipulation) has been analysed mainly by psychologists. This phenomenon has not been studied in linguistics yet. The author of the article gives a linguotypological description of the verbal countermanipulation tactics as exemplified in political video blogs reviewing the events with the participation of A. Navalny. A special two-stage algorithm which included a communicative pragmatic analysis was used for revealing countermanipulative intention in political video blogs. The first stage included attentive viewing of the videos and their analysis to determine manipulation upon certain criteria (a hidden aim, use of non-cooperative strategies and tactics and special verbal manipulative techniques). The second stage consisted of analysing the response utterances to define countermanipulative intention (neutralising manipulation), identification of countermanipulative tactics, their definition and classification. As a result of the conducted research, the author of the article has distinguished two groups of countermanipulative tactics: overt opposition tactics and covert opposition tactics. The group of overt opposition tactics includes the tactic of manipulative intention revealing, the tactic of making a question about manipulator’s intentions, the tactic of manipulation technique revealing, the tactic of counterargumentation and the tactic of refusing to change one’s behaviour towards manipulator’s intentions. The covert opposition tactics are the tactic of clarification questions and the tactic of repeating the manipulator’s words. The author points out the importance of further study of verbal countermanipulation from the perspective of solving the problems of the personal and social information security.

Bank Portfolio Management under Credit Market Imperfections

This paper examines bank portfolio management under banking regulation and asymmetric information about borrower types and screening by banks and imperfect competition in the credit market. A bank tries to maximize expected profit subject to a portfolio variance constraint. The analysis yields the following results: For a monopoly bank, the incentive constraint of the efficient type of borrowers will be binding and the participation constraint of the inefficient type of borrowers will be binding. Further, given the variance constraint being binding, the optimal portfolio will be on the efficiency frontier. The paper also examines duopoly competition between aggressive (predator) and defensive (prey) banks and the scope for potential cooperation and reveals that among the alternatives of natural monopoly, entry deterrence, takeovers and efficient portfolio diversification through mergers or interest swaps, the cooperative efficient portfolio diversification strategy will dominate any non-cooperative strategy whenever portfolio returns are negatively correlated between any pair of interacting banks as it reduces portfolio variance for a given package of interest and loans.