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Exploration in NetHack using occupancy maps

Published:14 August 2017Publication History

ABSTRACT

Roguelike games generally feature exploration problems as a critical, yet often repetitive element of gameplay. Automated approaches, however, face challenges in terms of optimality. This paper presents an approach to exploration of roguelike dungeon environments. Our design, based on the concept of occupancy maps popular in robotics, aims to minimize exploration time, balancing coverage with resource cost. Through extensive experimentation on NetHack maps we show that this technique is significantly more efficient than simpler greedy approaches. Results point towards better automation for players as well as heuristics for fully automated gameplay.

References

  1. Muntasir Chowdhury and Clark Verbrugge. 2016. Exhaustive Exploration Strategies for NPCs. In Proceedings of the 1st International Joint Conference of DiGRA and FDG: 7th Workshop on Procedural Content Generation.Google ScholarGoogle Scholar
  2. Héctor H. Gonzàlez-Baños and Jean-Claude Latombe. 2002. Navigation Strategies for Exploring Indoor Environments. International Journal of Robotics Research 21, 10--11 (2002), 829--848.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J. Hagelbäck and S. J. Johansson. 2008. Dealing with fog of war in a Real Time Strategy game environment. In Computational Intelligence in Games. 55--62. Google ScholarGoogle ScholarCross RefCross Ref
  4. Damián Isla. 2005. Probabilistic Target-Tracking and Search Using Occupancy Maps. In AI Game Programming Wisdom 3. Charles River Media.Google ScholarGoogle Scholar
  5. Damián Isla. 2013. Third Eye Crime: Building a Stealth Game Around Occupancy Maps. (2013). Artificial Intelligence and Interactive Digital Entertainment.Google ScholarGoogle Scholar
  6. Miguel Juliá, Arturo Gil, and Oscar Reinoso. 2012. A comparison of path planning strategies for autonomous exploration and mapping of unknown environments. Autonomous Robots 33, 4 (2012), 427--444. Google ScholarGoogle ScholarCross RefCross Ref
  7. S. Koenig, C. Tovey, and W. Halliburton. 2001. Greedy mapping of terrain. In IEEE Int Conf Robot Autom, Vol. 4. 3594--3599. Google ScholarGoogle ScholarCross RefCross Ref
  8. S. M. LaValle. 2006. Planning Algorithms. Cambridge University Press, Cambridge, U.K. Available at http://planning.cs.uiuc.edu/. Google ScholarGoogle ScholarCross RefCross Ref
  9. Hans Moravec. 1988. Sensor Fusion in Certainty Grids for Mobile Robots. AI Magazine 9, 2 (July 1988), 61--74.Google ScholarGoogle Scholar
  10. Hans Moravec and A. E. Elfes. 1985. High Resolution Maps from Wide Angle Sonar. In IEEE Int Conf Robot Autom. 116--121.Google ScholarGoogle Scholar
  11. NetHack Wiki. 2016. Comestible --- NetHack Wiki. https://nethackwiki.com/wiki/Comestible. (2016).Google ScholarGoogle Scholar
  12. B. Yamauchi. 1997. A frontier-based approach for autonomous exploration. In CIRA. 146--151. Google ScholarGoogle ScholarCross RefCross Ref

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  1. Exploration in NetHack using occupancy maps

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        cover image ACM Other conferences
        FDG '17: Proceedings of the 12th International Conference on the Foundations of Digital Games
        August 2017
        545 pages
        ISBN:9781450353199
        DOI:10.1145/3102071

        Copyright © 2017 Owner/Author

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 14 August 2017

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        Acceptance Rates

        FDG '17 Paper Acceptance Rate36of89submissions,40%Overall Acceptance Rate152of415submissions,37%

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