Adaptive functions in an agent-based model of an economic system

About this project

Agent based models, despite a history reaching back to the 1940s, have been recently cited as useful technique for planning economic development, recovering from the COVID pandemic, and simulating the effect of economic crashes. These models offer an insightful alternative to the traditional techniques of mathematical modelling.

The work presented in this project conducts a number of experiments comparing how system resilience is affected by two types of system adaptation, one where system-wide rule is applied to the pricing of goods, and another where individual agents have greater control over prices, based on their individual circumstances.

Results draw the conclusion that a self-adaptive function can provide greater stability, but resilience depends whether the measured variable is a primary or secondary variable to the adaptive function. Further observations are made on the instability caused by frequent changes in system state. This work will help to provide a better understanding for how measurements of resilience of simulations are taken, and present a number of avenues for future work.

Associated researcher

Dr David White

Senior Lecturer

Post Graduate Lead and Course Leader for MPhil / PhD in Games Technology. Senior Lecturer in Computer Games Programming – 3D graphics programming and AI.

David's profile
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Research Excellence Framework 2021

of Research is “Internationally Excellent” or “World Leading”

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