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## Summary
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This model demonstrates Mesa's ability to dynamically create new classes of agents that are composed of existing agents. These meta-agents inherits functions and attributes from their sub-agents and users can specify new functionality or attributes they want the meta agent to have. For example, if a user is doing a factory simulation with autonomous systems, each major component of that system can be a sub-agent of the overall robot agent. Or, if someone is doing a simulation of an organization, individuals can be part of different organizational units that are working for some purpose.
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This model demonstrates Mesa's ability to dynamically create new classes of agents that are composed of existing agents. These meta-agents inherits functions and attributes from their sub-agents and users can specify new functionality or attributes they want the meta agent to have. For example, if a user is doing a factory simulation with autonomous systems, each major component of that system can be a sub-agent of the overall robot agent. Or, if someone is doing a simulation of an organization, individuals can be part of different organizational units that are working for some purpose.
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To provide a simple demonstration of this capability is an alliance formation model.
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To provide a simple demonstration of this capability is an alliance formation model.
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In this simulation n agents are created, who have two attributes (1) power and (2) preference. Each attribute is a number between 0 and 1 over a gaussian distribution. Agents then randomly select other agents and use the [bilateral shapley value](https://en.wikipedia.org/wiki/Shapley_value) to determine if they should form an alliance. If the expected utility support an alliances, the agent creates a meta-agent. Subsequent steps may add agents to the meta-agent, create new instances of similar hierarchy, or create a new hierarchy level where meta-agents form an alliance of meta-agents. In this visualization of this model a new meta-agent hierarchy will be a larger node and a new color.
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In this simulation n agents are created, who have two attributes (1) power and (2) preference. Each attribute is a number between 0 and 1 over a gaussian distribution. Agents then randomly select other agents and use the [bilateral shapley value](https://en.wikipedia.org/wiki/Shapley_value) to determine if they should form an alliance. If the expected utility support an alliances, the agent creates a meta-agent. Subsequent steps may add agents to the meta-agent, create new instances of similar hierarchy, or create a new hierarchy level where meta-agents form an alliance of meta-agents. In this visualization of this model a new meta-agent hierarchy will be a larger node and a new color.
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In its current configuration, agents being part of multiple meta-agents is not supported
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In its current configuration, agents being part of multiple meta-agents is not supported
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## Installation
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The full tutorial describing how the model is built can be found at:
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