tex216/Block-World

Python program that implements an agent that can solve Block World problems optimally (in the minimum number of moves) for an arbitrary initial arrangement of blocks (A-Z, 26 blocks maximum) using Generate & Test and Means-Ends Analysis techniques.

28
/ 100
Experimental

This helps artificial intelligence researchers and students develop and test planning algorithms. You provide a starting arrangement of blocks (A-Z, up to 26) and a target arrangement. It outputs the shortest possible sequence of moves to transform the initial setup into the goal. Anyone working with AI planning problems, especially in classical planning domains, would find this useful.

No commits in the last 6 months.

Use this if you need an optimal solution to the Block World problem to benchmark your own AI planning algorithms or to study optimal pathfinding.

Not ideal if you're looking for a general-purpose AI planning system for complex, real-world logistical or robotics tasks beyond the Block World domain.

AI planning problem solving pathfinding classical AI optimal control
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 16 / 25

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8

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6

Language

Python

License

Last pushed

Aug 28, 2021

Commits (30d)

0

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