Interactive Agent-Based Simulation for Experimentation: A Case Study with Cooperative Game Theory

Modelling ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 425-447
Author(s):  
Andrew J. Collins ◽  
Sheida Etemadidavan

Incorporating human behavior is a current challenge for agent-based modeling and simulation (ABMS). Human behavior includes many different aspects depending on the scenario considered. The scenario context of this paper is strategic coalition formation, which is traditionally modeled using cooperative game theory, but we use ABMS instead; as such, it needs to be validated. One approach to validation is to compare the recorded behavior of humans to what was observed in our simulation. We suggest that using an interactive simulation is a good approach to collecting the necessary human behavior data because the humans would be playing in precisely the same context as the computerized agents. However, such a validation approach may be suspectable to extraneous effects. In this paper, we conducted a correlation research experiment that included an investigation into whether game theory experience, an extraneous variable, affects human behavior in our interactive simulation; our results indicate that it did not make a significant difference. However, in only 42 percent of the trials did the human participants’ behavior result in an outcome predicted by the underlying theory used in our model, i.e., cooperative game theory. This paper also provides a detailed case study for creating an interactive simulation for experimentation.

Author(s):  
Mahsa Noori ◽  
Alireza Emadi ◽  
Ramin Fazloula

Abstract Despite the advancement of technical tools for the analysis of complex systems, the most important issue in solving water resource problems focuses on the interaction of human and natural systems. Agent-Based Model has been used as an effective tool for the development of integrated human and environmental models. One of the main challenges of this method is identifying and describing the main agents. In this study, three main approach including Genetic Algorithm, cooperative game theory and Agent-Based Model have been used to optimize water allocation in Tajan catchment. The proposed Agent-Based Model is a new equation for calculating stakeholder utility and simulating their interactions that can create a hydrological-environmental-human relationship for demand management and optimal water allocation. The results showed that the total benefit of cooperative game theory and Agent-Based Model relative to Genetic Algorithm has been increased 24 and 21% respectively. Although the total benefit in game theory is greater than the Agent-Based Model, but the Agent-Based Model considering the agents feedback propose a more comprehensive approach to optimal water allocation.


Author(s):  
Cunbin Li ◽  
Ding Liu ◽  
Yi Wang ◽  
Chunyan Liang

AbstractAdvanced grid technology represented by smart grid and energy internet is the core feature of the next-generation power grid. The next-generation power grid will be a large-scale cyber-physical system (CPS), which will have a higher level of risk management due to its flexibility in sensing and control. This paper explains the methods and results of a study on grid CPS’s behavior after risk. Firstly, a behavior model based on hybrid automata is built to simulate grid CPS’s risk decisions. Then, a GCPS risk transfer model based on cooperative game theory is built. The model allows decisions to ignore complex network structures. On this basis, a modified applicant-proposing algorithm to achieve risk optimum is proposed. The risk management model proposed in this paper can provide references for power generation and transmission decision after risk as well as risk aversion, an empirical study in north China verifies its validity.


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