Modelling Flashcards
Computer Modelling
using software abstractions to represent a real or virtual problem
Model
representation of a physical system or process. Simulate what is happening in the system that the model represents.
Computer model
block of code or logic that takes arguments and returns results. Sometimes referred to as black boxes, as users may only be interested in inputs and outputs and not the inner workings.
benefits of modelling
Allow us to gain knowledge and make predictions about the environment in a way that is frequently safer, cheaper and faster than real world experiments
-test feasability of idea
-make predictions
-offer solutions to a problem that can’t be solved analytically due to scale or complexity
ABM
Agent-based Modeling
Agent-Based Modeling
building models to simulate actions of individual agents within an environment. They are independent of each other and the environment. Environment contains multiple agents
What ABM allows
Investigate how specific attributes of an agent may affect other agents or the environment as a whole.
Benefits of ABM
-describes complex environments by applying a simple set of rules to each individuals behaviour
-can test specific scenarios before they happen
-easy to work out a basic set of rules even in a complex environment
Emergent behaviours
Behaviours observed in environment as a whole but not in individual agents. Only emerge when agents interact in the environment.
Example of agent based modeling
used to mimic and understand traffic in cities. Every car is an agent with its own traits. Cars can interact and react to things like traffic lights or accidents.
Benefits of example of ABM
-insight into traffic congestion and what causes it
-impact of a new road infrastructure on traffic
-come up with strategies for optimising traffic management
Emergent behaviour of ABM example
new road could allow more commuters to get to work on time
