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Projective Simulation (PS) is a framework for studying agency from a physical perspective. PS agents learn from interaction with their environment and base their decisions on episodic memory. Internally, their deliberation corresponds to random walks on a clip network (graph), which provides an interpretable route to physical realizations and analysis.
This library provides all the necessary tools to develop, deploy, and train PS agents in a variety of environments. Its content spans from entry-level tutorials that introduce the core principles of PS to cutting-edge research on the latest developments and applications. It is actively developed by the QIC group at UIBK.
Projective simulation is available for python>=3.10 via
pip install projective_simulationThis will also install the necessary library requirements.
To begin exploring Projective Simulation, we recommend starting with the tutorials, which cover topics from the basics to more advanced applications.
If you want to develop or deploy PS agents, please check the documentation.
If you found this package useful and used it in your projects, you can cite either the particular PS paper that you found most useful (see a list here) or use the following to cite the whole library:
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