Synergistic integration between machine learning and agent-based modeling: A multidisciplinary review

W Zhang, A Valencia, NB Chang - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Agent-based modeling (ABM) involves develo** models in which agents make adaptive
decisions in a changing environment. Machine-learning (ML) based inference models can …

A survey of inverse reinforcement learning

S Adams, T Cody, PA Beling - Artificial Intelligence Review, 2022‏ - Springer
Learning from demonstration, or imitation learning, is the process of learning to act in an
environment from examples provided by a teacher. Inverse reinforcement learning (IRL) is a …

[HTML][HTML] Agent decision-making: The Elephant in the Room-Enabling the justification of decision model fit in social-ecological models

N Wijermans, G Scholz, É Chappin… - … Modelling & Software, 2023‏ - Elsevier
Agent-based models are particularly suitable to reflect the dynamics of humans, nature, and
their interactions, making them a crucial approach for understanding social-ecological …

A framework proposal for machine learning-driven agent-based models through a case study analysis

Y Turgut, CE Bozdag - Simulation Modelling Practice and Theory, 2023‏ - Elsevier
Agent-based modeling (ABM) has been widely employed by researchers in various
domains. Develo** valid and useful agent-based models (ABMs) imposes challenges on …

[HTML][HTML] Generating synthetic bitcoin transactions and predicting market price movement via inverse reinforcement learning and agent-based modeling

K Lee, S Ulkuatam, P Beling… - Journal of Artificial …, 2018‏ - jasss.soc.surrey.ac.uk
In this paper, we present a novel method to predict Bitcoin price movement utilizing inverse
reinforcement learning (IRL) and agent-based modeling (ABM). Our approach consists of …

[PDF][PDF] Live simulations

S Swarup, HS Mortveit - … of the 19th International Conference on …, 2020‏ - aamas.csc.liv.ac.uk
The next exciting step for large-scaled, data-driven, agent-based simulations is to make
them live. In this article we describe what is meant by a live simulation, how this concept …

[HTML][HTML] Multi-agent learning of asset maintenance plans through localised subnetworks

MP Hernández, A Puchkova, AK Parlikad - Engineering Applications of …, 2024‏ - Elsevier
Maintenance planning of networked multi-asset systems is a complex problem due to the
inherent individual and collective asset constraints and dynamics as well as the size of the …

[PDF][PDF] Agent-based models using artificial intelligence: A literature review

M Hauff, A Lurz - 2022‏ - sce.carleton.ca
Simulations of behavior, in particular agent-based models (ABM), enhance informed
decision-making. At present, Covid-19's autonomous dispersion is a notable use case, but …

Big Data (R) evolution in Geography: Complexity Modelling in the Last Two Decades

L Perez, R Sengupta - Geography Compass, 2024‏ - Wiley Online Library
The use of data and statistics along with computational systems heralded the beginning of a
quantitative revolution in Geography. Use of simulation models (Cellular Automata and …

Bayesian inverse reinforcement learning for collective animal movement

TLJ Schafer, CK Wikle, MB Hooten - The Annals of Applied …, 2022‏ - projecteuclid.org
Bayesian inverse reinforcement learning for collective animal movement Page 1 The Annals
of Applied Statistics 2022, Vol. 16, No. 2, 999–1013 https://doi.org/10.1214/21-AOAS1529 © …