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-**Description**: This model introduces an adaptive strategy where the decision-making process incorporates learning from past experiences to refine the policy over time.
- A simple example which shows how to build up to a composite processor but with a small model
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- The notebook can be found [here](https://github.com/BlockScience/bdp-toy-examples/blob/main/Composite%20Processor%20Mini/Composite%20Process%20Mini.ipynb)
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### 5. Iterated Game with Learning
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-**Description**: An extension of the two-player game model where both players employ adaptive strategies, allowing them to learn and evolve their strategies over multiple iterations.
- An example of building up a composite processor with a larger subsystem
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- The notebook can be found [here](https://github.com/BlockScience/bdp-toy-examples/blob/main/Composite%20Processor%20Mini/Composite%20Process%20Mini.ipynb)
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- Placeholder for future full models represented in separate repositories
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1. Homicidal Chauffeur
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2. KOI?
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### Dynamical Systems
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- An example of how a saved JSON file can be loaded and used to display five different versions of dynamical systems
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- The notebook can be found [here](https://github.com/BlockScience/bdp-toy-examples/blob/main/Dynamical%20Systems/Dynamical%20Systems.ipynb)
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## Full Canonical examples
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### Homicidal Chauffeur (Work in Progress)
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- A canonical example based on the classic "Homicidal Chauffeur" problem
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- The repository can be found [here](https://github.com/BlockScience/homicidal-chauffeur-canonical-example)
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