Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning

In three linesNew approach for learning generalized policies in classical planning using Relational Graph Neural Networks (R-GNNs). Authors introduce efficient lookahead search encoding and relational abstraction to improve scalability on IPC 2023 benchmark. Results outperform classical planner LAMA.

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