Foundations of Artificial Intelligence (FAI) Group
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About this page. In our research area, the development of tools -- implemented problem-solving algorithms -- is essential to validate the practical effectiveness of algorithmic ideas. We provide source code downloads for many of the tools developed in our research, as well as benchmark collections we have designed for evaluating these tools. All downloadable material is free for research and educational purposes.

Most of our implementations are based on the Fast Downward (FD) platform, which has become the canonical -- highly efficient-- implementation basis for classical AI Planning research (we have also designed an FD extension for probabilistic planning, see below). We are regular contributors, devising for example some of the techniques -- merge-and-shrink abstractions, a method to compute lower bound heuristic functions to be used for optimal planning -- that were awarded in the 2011 IPC versions of Fast Downward.

Our implementations on other bases are much smaller in number, and are mostly older developments. The content below is therefore organized as a single section containing all non-FD implementations, and then several sections organizing FD-based implementations by research direction.


Tools not based on Fast Downward.


FD Partial Delete Relaxation.


FD Probabilistic Planning.


FD Star-Topology Decoupling.


FD Abstractions & Symmetries. To get the following code please contact Michael Katz.


Benchmarks.