{"type":"ScholarlyArticle","title":"Procedural Generation of Initial States of Sokoban","authors":[{"name":"Dâmaris S. Bento","slug":"damaris-s-bento","given":"Dâmaris S.","family":"Bento","affiliation":"Universidade Federal de Vic ¸osa , Brazil"},{"name":"André G. Pereira","slug":"andre-g-pereira","given":"André G.","family":"Pereira","affiliation":"Universidade Federal do Rio Grande do Sul , Brazil"},{"name":"Levi H. S. Lelis","slug":"levi-h-s-lelis","given":"Levi H. S.","family":"Lelis","affiliation":"Universidade Federal de Vic ¸osa , Brazil"}],"abstract":"Procedural generation of initial states of state-space search problems have applications in human and machine learning as well as in the evaluation of planning systems. In this paper we deal with the task of generating hard and solvable initial states of Sokoban puzzles. We propose hardness metrics based on pattern database heuristics and the use of novelty to improve the exploration of search methods in the task of generating initial states. We then present a system called Beta that uses our hardness metrics and novelty to generate initial states. Experiments show that Beta is able to generate initial states that are harder to solve by a specialized solver than those designed by human experts.","doi":"10.24963/ijcai.2019/646","url":"https://ijcai.org/proceedings/2019/646","pdf":"https://ijcai.org/proceedings/2019/0646.pdf","markdown":"https://ijcai.org/proceedings/2019/646.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/646","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Multidisciplinary Topics and Applications","track":"Main track","number":646,"pages":{"first":4651,"last":4657},"keywords":["Planning and Scheduling: Search in Planning and Scheduling","Heuristic Search and Game Playing: Heuristic Search","Multidisciplinary Topics and Applications: Computer Games","Multidisciplinary Topics and Applications: Interactive Entertainment"],"videos":[],"references":[{"position":1,"raw":"[Anderson et al., 1985] John R Anderson, C Franklin Boyle, and Brian J Reiser. Intelligent tutoring systems. Science, 228:456- 462, 1985.","title":"Intelligent tutoring systems","authors":"C John R Anderson, Brian J Franklin Boyle, Reiser","year":"1985","venue":"Science","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Arfaee et al., 2011] Shahab Jabbari Arfaee, Sandra Zilles, and Robert Craig Holte. Learning heuristic functions for large state spaces. Artificial Intelligence, 175:2075-2098, 2011.","title":"Learning heuristic functions for large state spaces","authors":"Shahab Jabbari Arfaee, Sandra Zilles, Robert Craig, Holte","year":"2011","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Culberson and Schaeffer, 1996] Joseph C. Culberson and Jonathan Schaeffer. Searching with pattern databases. In Canadian Con- ference on Artificial Intelligence, pages 402-416, 1996.","title":"Searching with pattern databases","authors":"Joseph C Culberson, Jonathan Schaeffer","year":"1996","venue":"Canadian Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Culberson, 1999] Joseph C. Culberson. Sokoban is PSPACE- Complete. In Fun With Algorithms, pages 65-76, 1999.","title":"Sokoban is PSPACE-Complete","authors":"C Joseph, Culberson","year":"1999","venue":"Fun With Algorithms","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Doran and Michie, 1966] Jim E Doran and Donald Michie. Ex- periments with the graph traverser program. In Royal Society of London A, volume 294, pages 235-259. The Royal Society, 1966.","title":"Experiments with the graph traverser program","authors":"Michie Doran, Jim E Doran, Donald Michie","year":"1966","venue":"Royal Society of London A","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Edelkamp, 2001] Stefan Edelkamp. Planning with pattern databases. In European Conference on Planning, pages 13-24, 2001.","title":"Stefan Edelkamp. Planning with pattern databases","authors":"Edelkamp","year":"2001","venue":"European Conference on Planning","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Felner et al., 2004] Ariel Felner, Richard E. Korf, and Sarit Hanan. Additive pattern database heuristics. Journal of Artificial Intelli- gence Research, 22:279-318, 2004.","title":"Additive pattern database heuristics","authors":"Ariel Felner, Richard E Korf, Sarit Hanan","year":"2004","venue":"Journal of Artificial Intelligence Research","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Hoffmann and Nebel, 2001] Jörg Hoffmann and Bernhard Nebel. The ff planning system: Fast plan generation through heuristic search. Journal of Artificial Intelligence Research, 14(1):253- 302, 2001.","title":"The ff planning system: Fast plan generation through heuristic search","authors":"Nebel Hoffmann, Jörg Hoffmann, Bernhard Nebel","year":"2001","venue":"Journal of Artificial Intelligence Research","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Holte et al., 2006] Robert C. Holte, Ariel Felner, Jack Newton, Ram Meshulam, and David Furcy. Maximizing over multiple pat- tern databases speeds up heuristic search. Artificial Intelligence, 170(16-17):1123-1136, 2006.","title":"Maximizing over multiple pattern databases speeds up heuristic search","authors":"Robert C Holte, Ariel Felner, Jack Newton, Ram Meshulam, David Furcy","year":"2006","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Holte et al., 2016] Robert C Holte, Ariel Felner, Guni Sharon, and Nathan R Sturtevant. Bidirectional search that is guaranteed to meet in the middle. In AAAI Conference on Artificial Intelligence, volume 16, pages 3411-3417, 2016.","title":"Bidirectional search that is guaranteed to meet in the middle","authors":"Ariel Robert C Holte, Guni Felner, Nathan R Sharon, Sturtevant","year":"2016","venue":"AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Jarušek and Pelánek, 2010] Petr Jarušek and Radek Pelánek. Dif- ficulty rating of sokoban puzzle. In Starting AI Researcher Sym- posium, pages 140-150, 2010.","title":"Petr Jarušek and Radek Pelánek. Difficulty rating of sokoban puzzle","authors":"Pelánek Jarušek","year":"2010","venue":"Starting AI Researcher Symposium","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Junghanns and Schaeffer, 2001] Andreas Junghanns and Jonathan Schaeffer. Sokoban: Enhancing general single-agent search methods using domain knowledge. Artificial Intelligence, 129:219-251, 2001.","title":"Sokoban: Enhancing general single-agent search methods using domain knowledge","authors":"Schaeffer Junghanns, Andreas Junghanns, Jonathan Schaeffer","year":"2001","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Justesen et al., 2018] Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius, and Sebastian Risi. Procedural level generation improves generality of deep re- inforcement learning. CoRR, abs/1806.10729, 2018.","title":"Procedural level generation improves generality of deep reinforcement learning","authors":"Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius, Sebastian Risi","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Kartal et al., 2016] Bilal Kartal, Nick Sohre, and Stephen J Guy. Data-driven sokoban puzzle generation with monte carlo tree search. In AAAI Conference on Artificial Intelligence and In- teractive Digital Entertainment, 2016.","title":"Data-driven sokoban puzzle generation with monte carlo tree search","authors":"Bilal Kartal, Nick Sohre, Stephen J Guy","year":"2016","venue":"AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Korf, 1985] Richard E. Korf. Depth-first iterative-deepening: An optimal admissible tree earch. Artificial Intelligence, 27(1):97- 109, 1985.","title":"Depth-first iterative-deepening: An optimal admissible tree earch","authors":"Richard E Korf","year":"1985","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Lelis et al., 2013] Levi H. S. Lelis, Sandra Zilles, and Robert C. Holte. Predicting the Size of IDA*'s Search Tree. Artificial In- telligence, pages 53-76, 2013.","title":"Predicting the Size of IDA*'s Search Tree","authors":"H S Levi, Sandra Lelis, Robert C Zilles, Holte","year":"2013","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Lelis et al., 2016] Levi H. S. Lelis, Roni Tzvi Stern, Shahab Jab- bari Arfaee, Sandra Zilles, Ariel Felner, and Robert Craig Holte. Predicting optimal solution costs with bidirectional stratified sampling in regular search spaces. Artificial Intelligence, 230:51- 73, 2016.","title":"Predicting optimal solution costs with bidirectional stratified sampling in regular search spaces","authors":"H S Levi, Roni Tzvi Lelis, Shahab Stern, Sandra Jabbari Arfaee, Ariel Zilles, Robert Felner, Holte Craig","year":"2016","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Lipovetzky and Geffner, 2012] Nir Lipovetzky and Héctor Geffner. Width and serialization of classical planning prob- lems. In European Conference on Artificial Intelligence, pages 540-545. IOS Press, 2012.","title":"Width and serialization of classical planning problems","authors":"Geffner Lipovetzky, Nir Lipovetzky, Héctor Geffner","year":"2012","venue":"European Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Lipovetzky and Geffner, 2017] Nir Lipovetzky and Hector Geffner. Best-first width search: Exploration and exploitation in classical planning. In AAAI Conference on Artificial Intelligence, pages 3590-3596, 2017.","title":"Best-first width search: Exploration and exploitation in classical planning","authors":"Geffner Lipovetzky, Nir Lipovetzky, Hector Geffner","year":"2017","venue":"AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Mariño and Lelis, 2016] Julian R. H Mariño and Levi H. S. Lelis. A computational model based on symmetry for generating vi- sually pleasing maps of platform games. In AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, pages 65-71, 2016.","title":"A computational model based on symmetry for generating visually pleasing maps of platform games","authors":"Julian R H Mariño, H S Levi, Lelis","year":"2016","venue":"AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Murase et al., 1996] Yoshio Murase, Hitoshi Matsubara, and Yuzuru Hiraga. Automatic making of sokoban problems. PRI- CAI: Topics in Artificial Intelligence, pages 592-600, 1996.","title":"Automatic making of sokoban problems","authors":"Yoshio Murase, Hitoshi Matsubara, Yuzuru Hiraga","year":"1996","venue":"PRI-CAI: Topics in Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Orseau et al., 2018] Laurent Orseau, Levi H. S. Lelis, Tor Latti- more, and Théophane Weber. Single-agent policy tree search with guarantees. In Advances in Neural Information Processing Systems, pages 3205-3215, 2018.","title":"Single-agent policy tree search with guarantees","authors":"Laurent Orseau, H S Levi, Tor Lelis, Théophane Lattimore, Weber","year":"2018","venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Pereira et al., 2015] André G Pereira, Marcus Ritt, and Luciana S Buriol. Optimal sokoban solving using pattern databases with specific domain knowledge. Artificial Intelligence, 227:52-70, 2015.","title":"Optimal sokoban solving using pattern databases with specific domain knowledge","authors":"G André, Marcus Pereira, Luciana S Ritt, Buriol","year":"2015","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Polozov et al., 2015] Oleksandr Polozov, Eleanor O'Rourke, Adam M. Smith, Luke Zettlemoyer, Sumit Gulwani, and Zoran Popovic. Personalized mathematical word problem generation. In International Joint Conference on Artificial Intelligence, pages 381-388. AAAI, 2015.","title":"Personalized mathematical word problem generation","authors":"Oleksandr Polozov, O' Eleanor, Adam M Rourke, Luke Smith, Sumit Zettlemoyer, Zoran Gulwani, Popovic","year":"2015","venue":"International Joint Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2015/60"},{"position":25,"raw":"[Pommerening et al., 2013] Florian Pommerening, Gabriele Röger, and Malte Helmert. Getting the most out of pattern databases for classical planning. In International Joint Conference on Artificial Intelligence, 2013.","title":"Getting the most out of pattern databases for classical planning","authors":"Pommerening","year":"2013","venue":"International Joint Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2013/347"},{"position":26,"raw":"[Racanière et al., 2017] Sébastien Racanière, Théophane Weber, David Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, et al. Imagination-augmented agents for deep reinforcement learning. In Advances in Neural Information Pro- cessing Systems, pages 5690-5701, 2017.","title":"Imagination-augmented agents for deep reinforcement learning","authors":"Sébastien Racanière, Théophane Weber, David Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li","year":"2017","venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Smith and Mateas, 2011] Adam M. Smith and Michael Mateas. Answer set programming for procedural content generation: A design space approach. IEEE Transactions on Computational In- telligence and AI in Games, 3(3):187-200, 2011.","title":"Answer set programming for procedural content generation: A design space approach","authors":"Adam M Smith, Michael Mateas","year":"2011","venue":"IEEE Transactions on Computational Intelligence and AI in Games","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Snodgrass and Ontañón, 2017] Sam Snodgrass and Santiago Ontañón. Player movement models for video game level genera- tion. In International Joint Conference on Artificial Intelligence, pages 757-763, 2017.","title":"Sam Snodgrass and Santiago Ontañón. Player movement models for video game level generation","authors":"Ontañón Snodgrass","year":"2017","venue":"International Joint Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Sturtevant and Ota, 2018] Nathan R. Sturtevant and Matheus Jun Ota. Exhaustive and semi-exhaustive procedural content genera- tion. In AAAI Conference on Artificial Intelligence and Interac- tive Digital Entertainment, pages 109-115, 2018.","title":"Exhaustive and semi-exhaustive procedural content generation","authors":"Nathan R Sturtevant, Matheus Jun, Ota","year":"2018","venue":"AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","doi":null,"url":null,"internal_url":null},{"position":30,"raw":"[Taylor and Parberry, 2011] Joshua Taylor and Ian Parberry. Proce- dural generation of sokoban levels. In International North Amer- ican Conference on Intelligent Games and Simulation, pages 5- 12, 2011.","title":"Joshua Taylor and Ian Parberry. Procedural generation of sokoban levels","authors":"Parberry Taylor","year":"2011","venue":"International North American Conference on Intelligent Games and Simulation","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}