Challenges, tasks, and opportunities in modeling agent-based complex systems

An, Li; Grimm, Volker; Sullivan, Abigail; Turner, B. L.; Malleson, Nicolas; Heppenstall, Alison; Vincenot, Christian E.; Robinson, Derek T.; Ye, Xinyue; Liu, Jianguo; Lindkvist, Emilie; Tang, Wenwu

doi:10.1016/j.ecolmodel.2021.109685

Cited by 115 publications

(56 citation statements)

References 119 publications

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“…This is important as incorporating human behavior has repeatedly been called a challenge for M&S, especially with the ABM and simulation community. 43,44 By being able to compare the simulated agent and humans, we begin the process of being able to validate the mechanisms used to simulate human behavior; using valid mechanisms is important for the meeting of the challenge of incorporating human behavior in simulation models. The paper also shows an example of the ABMSCORE approach, incorporated into an ABM of the glove game, emulating human behavior in the context of strategic group formation (to a limited degree).…”

Section: Discussionmentioning

confidence: 99%

“…An et al 1 state that ''A key to the further advancement of the theory of agent-based complex systems is a systematic development of theories of human behavior.'' In a more recent work, An et al 44 state that ABM adopts innovation from other modeling techniques, such as ecological method; however, ''modeling human decision and behavior remains a big challenge.'' Schulze et al 45 identify several challenges related to ABM of human behavior.…”

Section: Abmmentioning

confidence: 99%

“…41,42 However, Cheng et al 43 mentioned the current inability of ABM to model human behavior and new advances to ABM need to be made. An et al 1 state that “A key to the further advancement of the theory of agent-based complex systems is a systematic development of theories of human behavior.” In a more recent work, An et al 44 state that ABM adopts innovation from other modeling techniques, such as ecological method; however, “modeling human decision and behavior remains a big challenge.” Schulze et al 45 identify several challenges related to ABM of human behavior. One of these challenges is “in parameterizing human decision-making in ABMs,” especially for “empirically informing human decision-making in ABMs.” Another challenge the authors mentioned is “the quality assessment of the representation of decision-making, particularly when modeling complex decision made by human agents.”…”

Section: Introductionmentioning

confidence: 99%

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Computerized agents versus human agents in finding core coalition in glove games

2022

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One of the challenges for agent-based modeling is being able to incorporate human behavior. Human behavior is a multifaceted phenomenon, with strategic coalition formation being one form. A hybrid agent-based modeling approach, called ABMSCORE, has been derived to emulate strategic group formation. In this paper, we describe a simulation experiment to compare the ABMSCORE with actual human behavior. The comparison criterion is the respective rates of finding an ideal coalition. In our experimental design, we go to great lengths to ensure the similarity of the scenarios in the two trial types: trials with computerized agents only and trials involving human participants when one of the computerized agents is replaced by an actual human. We did this to limit the number of possible extraneous variables introduced into the experimental system. The scenario considered is the glove game, a standard cooperative game that has been previously used in human experiments. Our results indicate that the ABMSCORE model produces similar rates of finding the ideal coalition as the human players; however, there are some limitations. This research provides evidence for using the ABMSCORE modeling approach to model human strategic coalition formation in agent-based models.

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Section: Discussionmentioning

confidence: 99%

Section: Abmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Computerized agents versus human agents in finding core coalition in glove games

2022

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“…To calculate entropy and TE values based on individual node degree evolution, data was generated using the NetLogo agent-based simulation platform. The advances observed in the use of agent-based modeling (ABM) to represent social systems compared to traditional equation-based models, and their ability to mimic heterogenous subsystems, autonomous entities, and nonlinear relationships, affirmed the use of ABM [32]. Tracing back to the principles of complexity science, a system is a sum of its parts as a whole but not the other way around.…”

Section: Simulation Models Used To Apply the Metricsmentioning

confidence: 99%

Quantitative Characterization of Complex Systems—An Information Theoretic Approach

Akundi

Smith

2021

ASI

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A significant increase in System-of-Systems (SoS) is currently observed in the social and technical domains. As a result of the increasing number of constituent system components, Systems of Systems are becoming larger and more complex. Recent research efforts have highlighted the importance of identifying innovative statistical and theoretical approaches for analyzing complex systems to better understand how they work. This paper portrays the use of an agnostic two-stage examination structure for complex systems aimed towards developing an information theory-based approach to analyze complex technical and socio-technical systems. Towards the goal of characterizing system complexity with information entropy, work was carried out in exploring the potential application of entropy to a simulated case study to illustrate its applicability and to establish the use of information theory within the broad horizon of complex systems. Although previous efforts have been made to use entropy for understanding complexity, this paper provides a basic foundation for identifying a framework to characterize complexity, in order to analyze and assess complex systems in different operational domains.

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“…A key issue that is limiting the development and use of computer models for simulating geographical systems, is related to their performance and scalability [4,17]. Increasingly, more information relevant for use in computer models are becoming available.…”

Section: A M O D E L L I N G F R a M E W O R K F O R S I M U L A T I ...mentioning

confidence: 99%

A modelling framework for simulating large geographical systems of agents and fields

Jong¹

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Challenges, tasks, and opportunities in modeling agent-based complex systems

Cited by 115 publications

References 119 publications

Computerized agents versus human agents in finding core coalition in glove games

Computerized agents versus human agents in finding core coalition in glove games

Quantitative Characterization of Complex Systems—An Information Theoretic Approach

A modelling framework for simulating large geographical systems of agents and fields

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