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Key concepts in simulation and modeling explained
Agent-Based Modeling
ABMs situate entities in virtual environments, or digital twins, in order to help better understand how the behavior of agents changes under varying conditions, and itself can impact broader systems.
Data Mining
Data Mining is a process applied to find unknown patterns, correlations, and anomalies in data. Through mining, meaningful insights can be extracted from data.
Deep Reinforcement Learning
DRL is a subset of Machine Learning in which agents are allowed to solve tasks on their own, and thus discover new solutions independent of human intuition.
Discrete Event Simulation
DES is a modeling approach that focuses on the occurrence of events in a simulation, separately and instantaneously, rather than on any chronological-scale.
Process Mining
Process mining is an application of data mining with the purpose of mapping an organization’s processes. It is used to optimize operations, and identify weaknesses.
Simulation Modeling
Simulation Models seek to demonstrate what happens to environments and agents within them, over time, under varying conditions.
