mlsanityData to 7 Oct 2026

Automated Synthesis of Steady-State Continuous Processes using Reinforcement Learning

arXiv 2101.04422 ↗First posted 12 Jan 2021cs.CE cs.AI cs.LGcited by 10

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Abstract (arXiv)

Automated flowsheet synthesis is an important field in computer-aided process engineering. The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis without any heuristics of prior knowledge of conceptual design. The environment consists of a steady-state flowsheet simulator that contains all physical knowledge. An agent is trained to take discrete actions and sequentially built up flowsheets that solve a given process problem. A novel method named SynGameZero is developed to ensure good exploration schemes in the complex problem. Therein, flowsheet synthesis is modelled as a game of two competing players. The agent plays this game against itself during training and consists of an artificial neural network and a tree search for forward planning. The method is applied successfully to a reaction-distillation process in a quaternary system.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 3 of its 36 references that are in the map. First posted on arXiv 12 Jan 2021.

Builds on

3 of 36 references.

References · 3

  1. 2015Deep Reinforcement Learning in Parameterized Action Spacecited by 65
  2. 2018Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Spacecited by 54
  3. 2020Continuous-Discrete Reinforcement Learning for Hybrid Control in Roboticscited by 42

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 4; 2024: 0; 2025: 1; 2026: 2.

10 papers.

  1. 2022Flowsheet synthesis through hierarchical reinforcement learning and graph neural networkscited by 10
  2. 2022Learning from flowsheets: A generative transformer model for autocompletion of flowsheetscited by 10
  3. 2023Deep reinforcement learning for process design: Review and perspectivecited by 9
  4. 2023Transfer learning for process design with reinforcement learningcited by 4
  5. 2023Policy-Based Self-Competition for Planning Problemscited by 3
  6. 2026Sketch2Simulation: Automating Flowsheet Generation via Multi Agent Large Language Modelscited by 3
  7. 2022Synthesis of separation processes with reinforcement learningcited by 2
  8. 2025Federated Learning from Molecules to Processes: A Perspectivecited by 2
  9. 2023Deep reinforcement learning uncovers processes for separating azeotropic mixtures without prior knowledgecited by 0
  10. 2026Enhanced Reinforcement Learning-based Process Synthesis via Quantum Computingcited by 0