Transforming and Encoding FTS for SAT Solving: What Helps, What Hurts (Extended Version)
Quick Answer
This study explores encoding factored tasks in SAT, proposing various strategies for translating factored transition relations into propositional logic.
Quick Take
It highlights the potential for improved performance in SAT-based planners through parallelism and task transformations, moving beyond traditional heuristic search methods.
Key Points
- Factored tasks extend SAS+ with disjunctive preconditions and conditional effects.
- Existing planning approaches primarily rely on heuristic search methods.
- The study proposes multiple encoding strategies for factored tasks in SAT.
- Parallelism can be exploited at various levels to enhance performance.
- Common task transformations impact the efficiency of SAT-based planners.
Paper Resources
Article Excerpt
From source RSS / original summaryarXiv:2605. 30563v1 Announce Type: new Abstract: Factored tasks are a classical planning representation that extends SAS+ with limited forms of disjunctive preconditions, conditional effects, and angelic nondeterminism. This allows for a more compact representation of tasks than traditional formalisms such as STRIPS or SAS+, and supports a wide range of task transformations. However, existing planning approaches for factored tasks have been limited to heuristic search methods.
In this work, we investigate how to encode factored tasks in SAT. We propose several ways to encode the tasks, focusing on different strategies for translating the factored transition relation into propositional logic. We also analyze how to exploit parallelism at various levels in this setting and study the impact of common task transformations on the performance of SAT-based planners.
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