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

Andrew J Collins,Sheida Etemadidavan

doi:10.3390/modelling2040023

Abstract

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.

Highlights

The nature of humans as autonomous interacting agents who change their behavior by adapting and learning in their environment makes their study difficult
The consistency of computerized agent decisions and human decisions on whether computerized agents make the same decisions as humans to join a coalition or not and make the same coalition suggestion or not was discussed in Collins et al [18], and the results indicated that our heuristic algorithm was consistent with that of human decisions and the consistency was higher in the group of humans with game theory experience
We suggest that an interactive simulation is a good approach to collecting the data on human behavior because the humans are playing in the exact same context as the computerized agents

Summary

Introduction

The nature of humans as autonomous interacting agents who change their behavior by adapting and learning in their environment makes their study difficult. We are interested in studying human decisions concerning strategic coalition formation. Different modeling methods exist to study this form of human behavior in a CAS context, for example, agentbased modeling [3] and game theory [4]. Cooperative game theory (1) focuses on games involving more than two players, and (2) focuses on coalition formation and how the payoffs will be distributed amongst the coalition members [19]. Many solution mechanisms have been proposed in cooperative game theory; the main two are the core [20] and the Shapley value [21]. The core of a cooperative game represents the coalition structure of the players, where no subgroup of players has an incentive to form a new coalition. To give a deeper understanding of the core concept, we will give some examples when we introduce the glove game

Methods

Results

Conclusion