A Multi-Agent Motion Prediction and Tracking Method Based on Non-Cooperative Equilibrium

A Multi-Agent Motion Prediction and Tracking method based on non-cooperative equilibrium (MPT-NCE) is proposed according to the fact that some multi-agent intelligent evolution methods, like the MADDPG, lack adaptability facing unfamiliar environments, and are unable to achieve multi-agent motion prediction and tracking, although they own advantages in multi-agent intelligence. Featured by a performance discrimination module using the time difference function together with a random mutation module applying predictive learning, the MPT-NCE is capable of improving the prediction and tracking ability of the agents in the intelligent game confrontation. Two groups of multi-agent prediction and tracking experiments are conducted and the results show that compared with the MADDPG method, in the aspect of prediction ability, the MPT-NCE achieves a prediction rate at more than 90%, which is 23.52% higher and increases the whole evolution efficiency by 16.89%; in the aspect of tracking ability, the MPT-NCE promotes the convergent speed by 11.76% while facilitating the target tracking by 25.85%. The proposed MPT-NCE method shows impressive environmental adaptability and prediction and tracking ability.

An Interactive Self-Learning Game and Evolutionary Approach Based on Non-Cooperative Equilibrium

Most current studies on multi-agent evolution based on deep learning take a cooperative equilibrium strategy, while interactive self-learning is not always considered. An interactive self-learning game and evolution method based on non-cooperative equilibrium (ISGE-NCE) is proposed to take the benefits of both game theory and interactive learning for multi-agent confrontation evolution. A generative adversarial network (GAN) is designed combining with multi-agent interactive self-learning, and the non-cooperative equilibrium strategy is well adopted within the framework of interactive self-learning, aiming for high evolution efficiency and interest. For assessment, three typical multi-agent confrontation experiments are designed and conducted. The results show that, first, in terms of training speed, the ISGE-NCE produces a training convergence rate of at least 46.3% higher than that of the method without considering interactive self-learning. Second, the evolution rate of the interference and detection agents reaches 60% and 80%, respectively, after training by using our method. In the three different experiment scenarios, compared with the DDPG, our ISGE-NCE method improves the multi-agent evolution effectiveness by 43.4%, 50%, and 20%, respectively, with low training costs. The performances demonstrate the significant superiority of our ISGE-NCE method in swarm intelligence.

The role of nonzero conjectural variation in pollution abatement and output in the design of emission taxes

The presence of nonzero conjectural variations in pollution abatement and output make emission taxes less effective with respect to reducing emissions. This has implications for the characterization of the optimal emission tax, particularly in an international context where there are large asymmetries in pollution intensities. A higher degree of collusion in output between polluting firms results in higher emissions taxes in the non-cooperative equilibrium. In contrast, a higher degree of collusion in abatement between polluting firms results in lower emissions taxes in the non-cooperative equilibrium. These results rely on the presence of nonzero conjectural variations and large asymmetries in pollution intensities across countries. The analysis is relevant to the design of international environmental policy, including cases where countries face increasing global competition and damages from rising global emissions.

Application of game theory non-cooperative equilibrium method in construction project management informationization

Based on the comprehensive application and bibliometrical analysis of the non-cooperative equilibrium theory of game theory, this paper takes the construction project group as the research background, analyzes the obstacles to the application of management informatization in the construction project, and conducts a pair game study on the application of management informatization by single or group subjects. Aims to provide a valuable reference for the application of management information in construction projects, in line with the policy orientation, and has a certain practical significance. On the basis of combing the relevant literature on the application of management information in the field of construction industry and game analysis, this paper first analyzes the appeal, current situation and obstacles of the application of management information in construction projects. The game results show that there are specific management inspirations for different subjects: the designer should change the way of thinking, control the cost of management information application, and carry out in-depth communication with other subjects on building information to ensure consistency; Contractors need to improve their own ability to apply management information, but also to coordinate and control the relative importance of the three objectives, so that efforts can be more easily converted into positive results.

COVID Social Distancing and the Poor: An Analysis of the Evidence for England

Social distancing is a matter of individuals’ choices as well as of regulation. We analyse weekly panel data on such behaviour for English Upper Tier Local Authorities (UTLAs) from March to July 2020, paying attention to the influence of poverty, as measured by free school meals provision. Panel regressions suggest that, although more stringent regulation and slightly lagged local cases of infection increase social distancing, both effects are weaker in UTLAs with higher levels of poverty, in part because of poor housing, and also because shortage of money has forced the poor to keep working. Thus motivated, we develop a two-class (rich/poor) model, in which a Nash non-cooperative equilibrium arises from individual choices in a regulatory regime with penalties for non-compliance. The model yields results in keeping with the empirical findings, indicating the desirability of generous measures to furlough workers in low-paid jobs as a complement to the stringency of general regulation.

Rational Behavior in Dynamic Multicriteria Games

We consider a dynamic, discrete-time, game model where n players use a common resource and have different criteria to optimize. To construct a multicriteria Nash equilibrium the bargaining solution is adopted. To design a multicriteria cooperative equilibrium, a modified bargaining scheme that guarantees the fulfillment of rationality conditions is applied. The concept of dynamic stability is adopted for dynamic multicriteria games. To stabilize the multicriteria cooperative solution a time-consistent payoff distribution procedure is constructed. The conditions for rational behavior, namely irrational-behavior-proofness condition and each step rational behavior condition are defined for dynamic multicriteria games. To illustrate the presented approaches, a dynamic bi-criteria bioresource management problem with many players is investigated.

The Puzzle of Organizing Collective Action

This introductory chapter discusses the importance of studying the process of coalition building. The puzzle of collective mobilization lies at the root of all politics. Studying the construction of multilateral military coalitions trains this puzzle on the context of international security—the one area of international cooperation that has traditionally been perceived as the most difficult to sustain a cooperative equilibrium. Moreover, the specific techniques used to build multilateral military coalitions affect how wars are fought. On the battlefield, coalition operations are supposedly more successful than non-coalition endeavors. Multilateral coalition building also affects the prospect for peace. Most peacekeeping deployments today are coalition endeavors, and research suggests that the stronger their participants, particularly in terms of personnel numbers and equipment, the more effective the missions are likely to be. Finally, coalitions unleash important socialization dynamics among participating states. They create common battle experiences and shape threat perceptions, military doctrine, and strategy for years to come. Sometimes, participation in a coalition can radically change a country's political trajectory. Thus, this book uses a social-institutional theory and evidence from over eighty multilateral military coalitions to explain coalition-building practices.