Abstract
In the field of game playing, the focus has been on two-player games, such as Chess and Go, rather than on multi-player games, with dominant multi-player techniques largely being an extension of two-player techniques to an \(N\)-player environment. To address the problem of multiple opponents, we propose the merging of two previously unrelated fields, namely those of multi-player game playing and Adaptive Data Structures (ADS). We present here a novel move-ordering heuristic for a dominant multi-player game playing algorithm, namely the Best-Reply Search (BRS). Our enhancement uses an ADS to rank the opponents in terms of their respective threat levels to the player modeled by the AI algorithm. This heuristic, referred to as Threat-ADS, has been rigorously tested, and the results conclusively demonstrate that, while it cannot damage the performance of BRS, it performs better in all cases examined.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
For a complete overview of adaptive list mechanisms, the reader is referred to [1].
References
Albers, S., Westbrook, J.: Self-organizing data structures. In: Online Algorithms, pp. 13–51 (1998)
Corman, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 3rd edn., pp. 302–320. MIT Press, Upper Saddle River, NJ, USA (2009)
Gelly, S., Wang, Y.: Exploration Exploitation in Go: UCT for Monte-Carlo Go. In: Proceedings of NIPS’06, the 2006 Annual Conference on Neural Information Processing Systems (2006)
Gonnet, G.H., Munro, J.I., Suwanda, H.: Towards self-organizing linear search. In: Proceedings of FOCS’79, the 1979 Annual Symposium on Foundations of Computer Science, pp. 169–171 (1979)
Hester, J.H., Hirschberg, D.S.: Self-organizing linear search. ACM Computing Surveys 17, 285–311 (1985)
Knuth, D.E., Moore, R.W.: An analysis of alpha-beta pruning. Artificial Intelligence 6, 293–326 (1975)
Luckhardt, C., Irani, K.: An algorithmic solution of n-person games. In: Proceedings of the AAAI’86, pp. 158–162 (1986)
Rendell, P.: A universal Turing machine in Conway’s Game of Life. In: Proceedings of HPCS’11, the 2011 International Conference on High Performance Computing and Simulation, pp. 764–772 (2011)
Rivest, R.L.: On self-organizing sequential search heuristics. In: Proceedings of the 1974 IEEE Symposium on Switching and Automata Theory, pp. 63–67 (1974)
Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn., pp. 161–201. Prentice-Hall, Inc., Upper Saddle River, NJ, USA (2009)
Schadd, M.P.D., Winands, M.H.M.: Best Reply Search for multiplayer games. IEEE Transactions on Computational Intelligence and AI in Games 3, 57–66 (2011)
Schaeffer, J.: The history heuristic and alpha-beta search enhancements in practice. IEEE Transactions on Pattern Analysis and Machine Intelligence 11, 1203–1212 (1989)
Shannon, C.E.: Programming a computer for playing Chess. Philosophical Magazine 41, 256–275 (1950)
Sleator, D.D., Tarjan, R.E.: Amortized efficiency of list update and paging rules. Communications of the ACM 28, 202–208 (1985)
Sturtevant, N.: A comparison of algorithms for multi-player games. In: Proceedings of the Third International Conference on Computers and Games, pp. 108–122 (2002)
Sturtevant, N.: Multi-player games: Algorithms and approaches. Ph.D. thesis, University of California (2003)
Sturtevant, N., Bowling, M.: Robust game play against unknown opponents. In: Proceedings of AAMAS’06, the 2006 International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 713–719 (2006)
Sturtevant, N., Zinkevich, M., Bowling, M.: Prob-Maxn: Playing n-player games with opponent models. In: Proceedings of AAAI’06, the 2006 National Conference on Artificial Intelligence, pp. 1057–1063 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Polk, S., Oommen, B.J. (2013). On Applying Adaptive Data Structures to Multi-Player Game Playing. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXX. SGAI 2013. Springer, Cham. https://doi.org/10.1007/978-3-319-02621-3_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-02621-3_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02620-6
Online ISBN: 978-3-319-02621-3
eBook Packages: Computer ScienceComputer Science (R0)