Master's thesis, M.Sc. Data Science · Leuphana University Lüneburg

From Reactive Control to Holistic Planning: Evolutionary Prompt Optimization for Hybrid Deterministic-Neural Agents in Long-Horizon Environments

King Wai Siu · supervised by Prof. Dr. Ricardo Usbeck and Prof. Dr. Burkhardt Funk

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Front matter

  1. Abstract
  2. Nomenclature

Chapters

  1. Chapter 1Introduction
  2. Chapter 2Foundations
  3. Chapter 3Related Work
  4. Chapter 4Task and Environment
  5. Chapter 5Method
  6. Chapter 6Experiments
  7. Chapter 7Discussion and Conclusion

References and declaration

  1. Bibliography
  2. Note on AI Usage

Appendices

  1. Appendix APrompts and Observation
  2. Appendix BCombat Rules, Exact Solver and Floors
  3. Appendix CThe Evaluation Platform
  4. Appendix DConfiguration and Result Files
  5. Appendix EValidity Incidents
  6. Appendix FPrompt Lineage
  7. Appendix GReasoning Excerpts

Cite

Siu, K. W. (2026). From Reactive Control to Holistic Planning: Evolutionary Prompt Optimization for Hybrid Deterministic-Neural Agents in Long-Horizon Environments. Master's thesis, Leuphana University Lüneburg.

@mastersthesis{siu2026magictower,
  author = {Siu, King Wai},
  title  = {From Reactive Control to Holistic Planning: Evolutionary Prompt Optimization for Hybrid Deterministic-Neural Agents in Long-Horizon Environments},
  school = {Leuphana University Lüneburg},
  type   = {Master's thesis (M.Sc. Data Science)},
  year   = {2026},
  url    = {https://github.com/thetobysiu/mt-thesis}
}