An Adversarial Agent-Based Design Method Using Stochastic Stackelberg Game Conditions

2021 ◽  
Vol 143 (3) ◽  
Author(s):  
Sean C. Rismiller ◽  
Jonathan Cagan ◽  
Christopher McComb
Keyword(s):  
Stackelberg Game ◽  
Design Method ◽  
Agent Based ◽  
Game Format ◽  
Game Theoretic

Abstract Products must often endure challenging conditions while fulfilling their intended functions. Game-theoretic methods can readily create a wide variety of these conditions to consider when creating designs. This work introduces Cognitively Inspired Adversarial Agents (CIAAs) that use a Stackelberg game format to generate designs resistant to these conditions. These agents are used to generate designs while considering a multidimensional attack. Designs are produced under these adversarial conditions and compared to others generated without considering adversaries to confirm the agents’ performance. The agents create designs able to withstand multiple combined conditions.

Stackelberg Game Theoretic Framework in Cognitive Green Heterogeneous Networks

2017 ◽  
pp. 269-286
Author(s):  
Chungang Yang ◽  
Pengyu Huang ◽  
Jia Xiao ◽  
Lingxia Wang ◽  
Jiandong Li
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Cognitive Radio ◽  
Cellular Networks ◽  
Communication Networks ◽  
Cognitive Radio Networks ◽  
Stackelberg Game ◽  
Radio Networks ◽  
Heterogeneous Cellular Networks ◽  
Game Theoretic

Game theory has found an extensive application in wireless communication networks including cognitive radio networks, heterogeneous cellular networks, cooperative relay networks. Also, cognitive radio networks, green communications and heterogeneous cellular networks have attracted a wide attention on improve the spectrum efficiency and energy efficiency; therefore, the capacity, the coverage and the energy consumption. However, interference problem and energy consumption are critical for these networks. Introducing hierarchy among different decision-making players in cognitive, heterogeneous, green, cooperative cellular networks can both save energy and mitigate interference, thus enhance throughput. Stackelberg game suits to model, analyze and design the distributed algorithms in these hierarchical decision-making networking scenarios. In this chapter, we introduce basics of Stackelberg game and survey the extensive applications of Stackelberg game in cognitive, heterogeneous, cooperative cellular networks with the emphasis on resource management, green commutations design and interference management. This chapter highlights the potentials and applications with the promising vision of Stackelberg game theoretic framework for future cognitive green heterogeneous cellular networks.

scholarly journals A Game Theoretic Approach for Eco-Design and Remanufacturing Considering Take-Back Policy

2020 ◽  
Vol 12 (17) ◽  
pp. 7174
Author(s):  
Xiaoxiao Chang ◽  
Guangye Xu ◽  
Qian Wang ◽  
Yongguang Zhong
Keyword(s):  
Environmental Impact ◽  
Stackelberg Game ◽  
Theoretic Approach ◽  
Subsidy Policy ◽  
Monetary Value ◽  
Game Equilibrium ◽  
Take Back ◽  
Game Theoretic ◽  
The Government ◽  
Game Theoretic Approach

This paper mainly aims at investigating the governments’ take-back policy of penalty or subsidy that motivates eco-design or remanufacturing. For this purpose, we consider a two-stage Stackelberg game between a government and a manufacturer. The government first decides to impose a take-back penalty or offer a take-back subsidy, and then the manufacturer selects to remanufacture or invest in eco-design as a response to the take-back policy. Upon analyzing and comparing game equilibrium, we find that the government prefers to offer a subsidy policy for eco-design and to impose a penalty policy for remanufacturing. The manufacturer will decide on investing in eco-design when the monetary value of the environmental impact of landfill and eco-design coefficient is medium. However, if the eco-design coefficient is high, the manufacturer practices remanufacturing instead of eco-design whether penalized and subsidized. The present study provides a set of guidelines in practical managerial recommendations for governments and manufacturers.

scholarly journals Evolutionary Game Analysis of Competitive Information Dissemination on Social Networks: An Agent-Based Computational Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Qing Sun ◽  
Zhong Yao
Keyword(s):  
Social Networks ◽  
Information Dissemination ◽  
Evolutionary Game ◽  
Theoretic Model ◽  
Game Analysis ◽  
Agent Based ◽  
Related Information ◽  
Game Theoretic ◽  
Adoption And Diffusion ◽  
Information Adoption

Social networks are formed by individuals, in which personalities, utility functions, and interaction rules are made as close to reality as possible. Taking the competitive product-related information as a case, we proposed a game-theoretic model for competitive information dissemination in social networks. The model is presented to explain how human factors impact competitive information dissemination which is described as the dynamic of a coordination game and players’ payoff is defined by a utility function. Then we design a computational system that integrates the agent, the evolutionary game, and the social network. The approach can help to visualize the evolution of % of competitive information adoption and diffusion, grasp the dynamic evolution features in information adoption game over time, and explore microlevel interactions among users in different network structure under various scenarios. We discuss several scenarios to analyze the influence of several factors on the dissemination of competitive information, ranging from personality of individuals to structure of networks.

Strategic Design Decisions for Uncertain Market Systems Using an Agent Based Approach

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Z. Wang ◽  
S. Azarm ◽  
P. K. Kannan
Keyword(s):  
Product Design ◽  
Theoretic Approach ◽  
Competitive Strategies ◽  
Market System ◽  
Design Decisions ◽  
Learning Behaviors ◽  
Agent Based ◽  
Strategic Design ◽  
Game Theoretic ◽  
Design For Market Systems

Market players, such as competing manufacturing firms and retail channels, can significantly influence the demand and profit of a new product. Existing methods in design for market systems use game theoretic models that can maximize a firm’s profit with respect to the product design and price variables given the Nash equilibrium of the market system. However, in the design for uncertain market systems, there is seldom equilibrium with players having fixed strategies in a given time period. In this paper, we propose an agent based approach for design for market systems that accounts for learning behaviors of the market players under uncertainty. By learning behaviors we mean that market players gradually, over time, learn to play with better strategies based on action–reaction behaviors of other players. We model a market system with agents representing competing manufacturers and retailers who possess learning capabilities and based on some prespecified rules are able to react and make decisions on the product design and pricing. The proposed agent based approach provides strategic design and pricing decisions for a manufacturing firm in response to possible reactions from market players in the short and long term horizons. Our example results show that the proposed approach can produce competitive strategies for the firm by simulating market players’ learning behaviors when they react only by setting prices, as compared to a game theoretic approach. Furthermore, it can yield profitable product design decisions and competitive strategies when competing firms react by changing design variables in the short term—case for which no previous method in design for market systems has been reported.

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