This page contains references to technic/scientific articles and books with Sokoban as a at least not insignificant part. If possible the source is provided.

The references in the documents have been explored for further publications about Sokoban. Not vigoriously but the chance are small that you will find major works not on the list below.

Please inform me if you have knowledge otherwise.

  1. icon-external-link Ashlock, Daniel and Schonfeld, Justin: Evolution for automatic assessment of the difficulty of sokoban boards. IEEE Congress on Evolutionary Computation, 2010
  2. icon-external-link Berger, Matthew S. and Lawton, James H.: Multi-agent Planning in Sokoban, CEEMAS 07, Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V, pg 334-336, Springer Verlag, 2007
  3. icon-file-text-o Botea, A., Müller, M. and Schaeffer, J.: Using abstraction for planning in Sokoban. Department of Computing Science, University of Alberta, Edmonton, Canada 2002
  4. icon-file-text-o Cazenave, Tristan and Jouandeau, Nicolas: Towards deadlock free sokoban. Board Games Studies Colloquium, Paris, France, page 12, 2010.
  5. icon-file-text-o Checa, Juan A. M.: The Sokoban Challenge – An analysis on past, present, and trends in algoirthms and heuristics for automatic solving of Sokoban problems. Computer Science Department, Campus Teatinos, University of Malaga, Spain, 2010
  6. icon-file-text-o Culbertson, J.C.: Sokoban is PSPACE-complete. Department of Computing Science, University of Alberta, Edmonton, Canada. 1997.
  7. icon-external-link Damgaard, B.: Sokoban Optimizer “scribbles” about the YASO optimizer., 2010.
  8. icon-external-link Damgaard, B.: Sokoban Solver “scribbles” about the YASS solver., 2010.
  9. icon-file-text-o Demaine, E.D. and Hoffmann, M.: Pushing blocks is NP-complete for noncrossin solution paths. Proceedings of the 13th Canadian Conference on Computational Geometry. 2001: 65-68.
  10. icon-file-text-o Demaine, E. D., Demaine, M.L., Hoffmann, M. and O’Rourke, J.: Pushing Blocks is Hard. Preprint to Elsevier Science. 2002.
  11. icon-file-text-oDemaine, E. D., Hearn, R. A. and Hoffmann, M: Push-2-F is PSPACE-Complete. Proceedings of the 14th Canadian Conference on Computational Geometry, Lethbridge, Alberta, Canada, August 12–14, 2002: 31–35.
  12. icon-file-text-o Demaret, Jean-Noel: L’intelligence artificielle et les jeux – Cas du Sokoban. Master thesis, University of Liege, 2007.
  13. icon-file-text-o Demaret, Jean-Noel, Lishout, Francois van and and Gribomont, Pascal: Hierarchical planning and learning for automatic solving of Sokoban problems. In 20th Belgium-Netherlands Conference on Artificial Intelligence, 57–64, 2008.
  14. icon-file-text-o Dor. D. and Zwick, U. Sokoban and other motion planning problems. Computational Geometry: Theory and Applications vol.13 iss.4, oct.1999
  15. icon-file-text-o Hänger, Beat: Phase Transitions in the Solvability of Sokoban. Bachelors Thesis. Department of Computer Science, Natural Science Faculty of the University of Basel, Germany, 2013
  16. icon-file-text-o Hearn, R. and Demaine, E.: PSPACE-Completeness of Sliding-Block Puzzles and Other Problems through the Nondeterministic Constraint Logic Model of Computation. November 2004.
  17. icon-file-text-o Hopcroft, J.E., Schwartz, J.T. and Sharir, M.: On the complexity of motion planning for multiple independent objects: PSPACE-hardness of the ‘Warehouseman’s Problem’. International Journal of Robotics Research, 3(4):76–88, 1984.
  18. icon-file-text-o Jarusek, Petr and, Pelanek Radek: Difficulty Rating of Sokoban Puzzle. Proceedings of the 2010 conference on STAIRS 2010, 140-150, 2010
  19. icon-file-text-o Jarusek, Petr and Pelanek, Radek: Human Problem Solving – Sokoban Case Study. Faculty of Informatics, Masaryk University, Brno, 2010
  20. icon-file-text-o Jarusek, Petr and Pelanek, Radek: What Determines Difficulty of Transport Puzzles? Proceedings of the 24. International Florida AI Research Society Conference, 2011
  21. icon-file-text-o Junghanns, Andreas and Schaeffer, Jonathan 1997. Sokoban: A challenging Single-Agent search problem. In IJCAI Workshop on Using Games as an Experimental Testbed for AI Reasearch, pages 2736.
  22. icon-file-text-o Junghanns, Andreas and Schaeffer, Jonathan, Relevance cuts: Localizing the search. In The First International Conference on Computers and Games, pages 113. 1998
  23. icon-file-text-o Junghanns, Andreas and Schaeffer, Jonathan, Single-Agent search in the presence of deadlocks. In AAAI, (1998), pages 419-424.
  24. icon-file-text-o Junghanns, Andreas and Schaeffer, Jonathan, Sokoban: Improving the search with relevance cuts. Journal of Theoretical Computing Science 252, 1998.
  25. icon-file-text-o Junghanns, Andreas and Schaeffer, Jonathan: Sokoban: Evaluating standard Single-Agent search techniques in the presence of deadlock. Advances in Artifial Intelligence, pages 115. 1998.
  26. icon-file-text-o Junghanns, Andreas, and Schaeffer, Jonathan: Domain-dependent single-agent search enhancements. In IJCAI, 570–577, 1999
  27. icon-file-text-o Junghanns, Andreas and Schaeffer, Jonathan: Sokoban – Enhancing
    general single-agent search methods using domain knowledge.
    Artificial Intelligence 129(1-2):219–251, 2001.
  28. icon-file-text-o Junghanns, Andreas. 1999. Pushing the Limits: New Developments
    in Single-Agent Search. Ph.D. Dissertation, University of
    Alberta, 1999.
  29. icon-file-text-o Kendall, G., Parkers, A. and Spoerer, K.: A Survey of NP-complete Puzzles. ICGA Journal. March 2008.
  30. icon-file-text-o Lishout, Francois van: Single-player games: Introduction to a new solving method combining classical state-space modelling with a multi-agent representation.  University of Liège, Liège, France, 2006
  31. icon-file-text-o Lishout, Francois van and Gribomont, Pascal: Single-player Games – Introduction to a New Solving Method Combining State-Space Modelling with a Multi-Agent Representation. DEA en sciences appliquées, University of Liège, Liège, France, 2006
  32. icon-file-text-o Murase, Y., Matsubara, H. and Hiraga, Y.: Automatic Making of Sokoban Problems. University of Library and Information Science, Tsukuba, Ibaraki, Japan, 1996(?)
  33. icon-file-text-o Odawara, Masaru; Kaneko, Tomoyuki and Kawai Satoru: A Method of
    Automatic Creation of Goal-Area in Sokoban Maps. Graduate School of Arts and Sciences, The University of Tokyo, Japan, 2003.
  34. icon-file-text-o Pereira,A.G.; Ritt,M.R.P. and Buriol,L.S. 2013. Finding Optimal Solutions to Sokoban Using Instance Dependent Pattern Databases. Proceedings of The Sixth International Symposium on Combinatorial Search, 141-148.
  35. icon-file-text-o Rei, Luis and Teixeira, Rui: Willy – A Sokoban Solving Agent. Faculdade de Engenharia da Universidade do Porto, Portugal 2014.
  36. icon-file-text-o Schaul, T., Evolving a compact, concept-based Sokoban solver. Master’s
    thesis, École Polytechnique Fédérale de Lausanne, May 2005.
  37. icon-file-text-o Takes, Frank: Sokoban – Reversed Solving. Bachelor’s thesis, Leiden Institute of Advanced Computer Science, January 2008.
  38. icon-file-text-o Takes, F., Sokoban: Reversed Solving. Leiden Institute of Advanced Computer Science, January 2008.
  39. icon-file-text-o Taylor, Joshua, Parsons, Thomas D. and Parberry, Ian: Comparing Player Attention on Procedurally Generated vs. Hand Crafted Sokoban Levels with an Auditory Stroop Test. Laboratory for Recreational Computing, Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA, 2015
  40. icon-file-text-o Taylor, Joshua and Parberry, Ian: Procedural Generation of Sokoban Levels, Proceedings of the 6th Annual North American Conference on AI and Simulation in Games, 5-12, 2011
  41. icon-file-text-o Virkkala,T.: Solving Sokoban. Masters Thesis. University of Helsinki, Department of Computer Science. 2011.
  42. W. Wesselink and H. Zantema. Shortest solutions for Sokoban. Proceedings of the 15th Netherlands/Belgium Coference on Artificial Intelligence p. 323-330, 2003
  43. icon-file-text-o Yoo, SungAe and Zellner, Ronald: Monitoring Sokoban Problem Solving – What a Case Study Implies for Metacognitive Support for Game-based Problem Solving? Texas A&M University, 2006.
  44. icon-file-text-o  Zhou, Neng-Fa and Dovier, Agostino: A Tabled Prolog Program for Solving Sokoban, Pescara, 2011