When both Grounding and not Grounding are Bad -- A Partially Grounded Encoding of Planning into SAT (Extended Version)

1. 1Identify the limitations of fully grounded and fully lifted planning approaches
2. 2Develop a partially grounded encoding that balances compactness and efficiency
3. 3Implement and evaluate three SAT encodings to demonstrate the effectiveness of the approach
4. 4Analyze the results to determine the optimal level of grounding for a given planning problem

AI engineers and researchers working on planning and SAT problems can benefit from this approach to improve the efficiency of their planning systems

💡 A middle ground between fully lifted and fully grounded planning can be achieved through partially grounded encoding

💡 Partially grounded encoding of planning into SAT can improve efficiency without sacrificing compactness