SmartSnake: An Adaptive Framework for Intelligent Control Synthesis

• Prashanth Chevva

  https://orcid.org/0009-0000-0147-5495

  Author

In this paper, we present SmartSnake, a flexible software environment based on Dionysos.jl for the intelligent synthesis of abstract-based control of complex dynamical systems. The platform offers tools that allow researchers and practitioners to design custom abstraction algorithms, which support partial state-space coverage and state-dependent controllers. The modular architecture of SmartSnake allows for an easy integration of machine learning and artificial intelligence to help develop future meta-solvers that will adapt intelligently to the structure of problems and overcome the curse of dimensionality as well. The solvers that can be utilized in SmartSnake are evaluated with respect to how practical they are and their computational efficiency for control synthesis scenarios. We will also present ongoing work on improvement of the platform with data-driven methods and heuristic symbolic models. SmartSnake provides a flexible framework for both reinforcement learning approaches and classical optimization of controllers.

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