laurimi/pydpomdp

Python package for Dec-POMDP files in the .dpomdp format

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Experimental

This package helps researchers and practitioners working with decentralized partially observable Markov decision processes (Dec-POMDPs) to easily access and manipulate problem definitions. It takes a Dec-POMDP problem definition in the standard .dpomdp file format as input. It provides direct access to problem components like agent details, state transitions, observation probabilities, and rewards, which can then be used for analysis or algorithm development. This is useful for AI researchers, robotics engineers, or anyone designing multi-agent systems.

No commits in the last 6 months.

Use this if you need to load and interact with existing Dec-POMDP problem files to analyze their properties or build algorithms on top of them.

Not ideal if you need to create new Dec-POMDP problem files, require support for factored or independent Dec-POMDPs, or need a full solver for these problems.

multi-agent systems reinforcement learning research AI planning robotics control decision-making under uncertainty
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 7 / 25

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Language

C++

License

GPL-3.0

Last pushed

Oct 28, 2022

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