Environment
The environment is the virtual world in which the agents act. It may be an entirely neutral medium with little or no effect on the agents, as in some agent-based models based on game theory, where the environment has no meaning. In other models, the environment may be as carefully designed as the agents themselves, as in some ecological or anthropological agent-based models where the environment represents complex geographical space that affects the agents’ behaviour. (Salgado&Gilbert, 2013). - Collection of patch
Introduction
Key concepts of environments are:
1. Spatial Representation
The environment may be represented in various ways, including grids, networks, continuous spaces, or abstract representations. The choice of spatial representation depends on the nature of the system being modeled and the level of detail required to capture its dynamics.
2. Resource Distribution
The environment typically contains resources or other entities that agents interact with or compete for. These resources could include food, energy, money, information, or any other relevant factors depending on the context of the model.
3. Dynamic Nature
The environment in an ABM can be dynamic, meaning that it may change over time in response to agent actions, external factors, or stochastic processes. Dynamic environments allow for the simulation of complex systems with evolving dynamics and feedback loops.
4. Constraints and Boundaries
The environment may impose constraints or boundaries on agent behavior, such as geographical barriers, legal regulations, or resource limitations. These constraints shape the opportunities and challenges faced by agents and influence their decision-making processes.
Explanation
Raster high and lower value
Vector point line polygon network
Dynamic : environments change over time during simulation
Static : environment does not change over time
Cellular automata key attributes:
- State variables : a set of attributes that describe the automaton at a particular point in time.
- Spatial framework: lattice of cells
- Neighbouthood structures : cell and neighbours
- Transition rules: rules that determine the state change
- Time: discrete steps
Examples
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Social:
The physical or virtual space where the crowd or individuals interact. It could be a simulated city, a social network, or a virtual world. -
Economic:
The market or economic system in which consumers and firms interact. It includes factors like supply and demand dynamics, prices, and resources available. -
Biological:
The ecosystem or habitat where animals or cells interact. It includes elements like the physical environment, resources, other organisms, and ecological dynamics. -
Transportation:
The road network or transportation system in which vehicles operate. It includes factors like traffic flow, traffic rules, infrastructure, and congestion. -
Multi-Agent Systems:
The distributed system or network where software agents operate. It includes factors like communication channels, data exchange protocols, and the infrastructure supporting agent interactions.
Schematic representation of an agent-based model (ABM). Source: Ramadiah, 2021.
Outgoing relations
- Environment is a feature of Agent based modelling
Incoming relations
- Cellular Automata is a feature of Environment
- Communication Environment is a kind of Environment
- Deterministic Environment is a kind of Environment
- Dynamic Environment is a kind of Environment
- Geographically Explicit Environment is a kind of Environment
- Physical Environment is a kind of Environment
- Spatially Explicit Environment is a kind of Environment
- Static Environment is a kind of Environment
- Stochastic Environment is a kind of Environment
- Environment Interaction is part of Environment
Contributors
- Ellen-Wien Augustijn
- Maria Perez