Statistical Issues in Agent-Based Models

Time: Tuesday 22-Sept-2020 16:00
Live in 2 days & 22:43:19


Motivation / Abstract
Agent-based models (ABMs) are computational models used to
simulate the actions and interactions of agents within a system.
Usually, each agent has a relatively simple set of rules for how it
responds to its environment and to other agents. These models are used
to gain insight into the emergent behavior of complex systems with many
agents, in which the emergent behavior depends upon the micro-level
behavior of the individuals. ABMs are widely used in many fields, and
this talk reviews some of those applications. However, as relatively
little work has been done on statistical theory for such models, this
talk also points out some of those gaps and recent strategies to address
Stream Categories:
 Math and Foundations

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