Agent Based Modeling, Mathematical Formalism for

Laubenbacher, Reinhard; Jarrah, Abdul Salam; Mortveit, Henning S.; Ravi, S. S.

doi:10.1007/978-1-4614-1800-9_6

Cited by 8 publications

(7 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can also be bottom-up, by extracting local parameters of a given ABM to obtain global parameters of inferred EBM. Several studies seem to be related to this way can be found in ( [15], [16]). In these contributions, the authors tried to abstract ABMs by introducing mathematical formalism [15] as well as moment approximations of ABMs [16].…”

Section: Introductionmentioning

confidence: 94%

“…Based on the case study, a dynamics of two competing species, we represent how to infer an EBM from a given ABM. Unlike in the previous studies ( [15], [16]), we extract local parameters to obtain global ones. For instance, we show that an EBM can be built from a given ABM by considering ABM as a virtual laboratory to test and to see effects of parameters.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Inferring Equation-Based Models from Agent-Based Models: A Case Study in Competition Dynamics

Nguyen

Taillandier

Drogoul

et al. 2012

Principles and Practice of Multi-Agent Systems

View full text Add to dashboard Cite

Two types of model, equation-based models (EBMs) and agentbased models (ABMs) are now widely used in modeling ecological complex systems and seem not to be reconciled. While ABMs can help in exploring and explaining the local causes of global phenomena, EBMs are useful for predicting their long-term evolution without having to explore them through simulated experiments. In this paper, we show that it is possible to use an ABM to infer an EBM. Base on the case study, a dynamics of two competing species, we illustrate our methodology through the presentation of two models: an ABM and an EBM. We also show that the two models give the same results on coexistence of the two competing species.

show abstract

Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Inferring Equation-Based Models from Agent-Based Models: A Case Study in Competition Dynamics

Nguyen

Taillandier

Drogoul

et al. 2012

Principles and Practice of Multi-Agent Systems

View full text Add to dashboard Cite

show abstract

“…In the broadest sense, an agent-based model (ABM) is a computational model of a target system in which autonomous agents governed by local rules interact with one another and with their environment [11,20]. These local rules determine how an agent's current state updates at discrete, incremental "time steps" over the course of an ABM simulation.…”

Section: Introductionmentioning

confidence: 99%

“…The objective of ABM development is typically to connect local agent interactions with system-level properties across both time and space such as population dynamics and self-organization. ABMs are found in virtually all areas of research [9,11,20], supported by a growing list of software [1] that range from general-purpose platforms such as NetLogo [21] and the PythonABM library [18] to specialized platforms like CompuCell3D [17], Morpheus [16], and PhysiCell [7] which aim to capture as many system details as possible in their implementation. In particular, the use of ABMs in the context of cellular biology has grown rapidly over the last decade [3,8,14,19] because of how cells can naturally be considered autonomous agents.…”

Section: Introductionmentioning

confidence: 99%

“…In most cases, the evaluation of ABMs against their associated systems is either too qualitative or too computationally expensive to be suitable for research fields like systems biology where the throughput of data acquisition is increasing while costs are decreasing. Qualitative evaluation typically relies on a visual comparison between simulated and collected data while quantitative evaluation involves running several simulations and performing statistical analysis to generate a measure of model "consistency" or "reproducibility"; the latter often requires significant computational resources and long simulation run-times [11,15]. As an alternative, several mathematical frameworks have been proposed over the years for formalizing ABMs, including finite dynamical systems, cellular automata, and Markov chains [9-11, 15, 22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating the Long-term Behavior of Biologically Inspired Agent-based Models

Cruz¹,

Toppen²,

Park³

et al. 2022

Preprint

View full text Add to dashboard Cite

An agent-based model (ABM) is a computational model in which the local interactions of autonomous agents with each other and with their environment give rise to global properties within a given domain. As the detail and complexity of these models has grown, so too has the computational expense of running several simulations to perform sensitivity analysis and evaluate long-term model behavior. Here, we generalize a framework for mathematically formalizing ABMs to explicitly incorporate features commonly found in biological systems: appearance of agents (birth), removal of agents (death), and locally dependent state changes. We then use our broader framework to extend an approach for estimating long-term behavior without simulations, specifically changes in population densities over time. The approach is probabilistic and relies on treating the discrete, incremental update of an ABM via "time steps" as a Markov process to generate expected values for agents at each time step. As case studies, we apply our extensions to both a simple ABM based on the Game of Life and a published ABM of rib development in vertebrates.

show abstract

Modeling sustainability transitions on complex networks

Tran¹

2014

Complexity

View full text Add to dashboard Cite

There has been renewed interest in sociotechnical systems in the context of transitioning to a more sustainable society. While gains have been made in the qualitative understanding of sustainable transitions and sociotechnical systems, these approaches have not been well-operationalized. Given the importance of meeting future energy and environmental policy targets, there is need to develop predictive techniques and more robust methods to quantify and analyze sociotechnical systems undergoing rapid change and uncertainty due to sustainability pressures. Sustainability transitions depend on largescale diffusion of technological and behavioral innovations on physical and virtual networked systems. Transitions can therefore be viewed as a subclass of diffusion phenomenon and subject to a range of mathematical and computational methods. We review, categorize, and critically assess methodological and theoretical approaches that integrate different aspects of sustainability, innovation, and complexity. We argue that these approaches should be adapted to improve our understanding of the behavior and dynamics of a broad range of sociotechnical systems to meet sustainability objectives. We therefore also make the conceptual link between complexity and sustainability as complimentary fields of research to inform policy and decision making to achieve more sustainable outcomes.

show abstract

Agent Based Modeling, Mathematical Formalism for

Cited by 8 publications

References 65 publications

Inferring Equation-Based Models from Agent-Based Models: A Case Study in Competition Dynamics

Inferring Equation-Based Models from Agent-Based Models: A Case Study in Competition Dynamics

Estimating the Long-term Behavior of Biologically Inspired Agent-based Models

Modeling sustainability transitions on complex networks

Contact Info

Product

Resources

About