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Research on Symbolic Design for Hybrid Discrete-Continuous Planning
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An arXiv paper proposes defining symbol usefulness from the perspective of solution algorithms: good symbols should expose discrete decisions that can simplify the solving of the original planning problem. The authors first introduce the concept of solver-sufficient symbolization for finite-horizon piecewise affine systems and design a counterexample-guided symbol invention algorithm, then extend it to optimization objectives that use general neural networks as energy functions. Simulation and real-world task experiments show that the resulting symbols reduce solving cost while maintaining solution quality, and improve interpretability and manipulability.
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- What Makes a Good Symbol for Hybrid Discrete-Continuous Planning?
The paper proposes defining symbol usefulness from the perspective of the solving algorithm: a good symbol should expose the discrete decisions that simplify solving the original planning problem. The authors first introduce the concept of solver-sufficient symbolization for finite-horizon piecewise-affine systems and design a counterexample-guided symbol invention algorithm, then extend it to optimization objectives whose energy functions are general neural networks. Experiments on simulated and real-robot tasks show that the resulting symbols reduce solving cost while maintaining solution quality, and improve interpretability and controllability.
arXiv cs.RO ·