Dana S. Nau

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Dana S. Nau, an American computer scientist and professor at the University of Maryland, College Park. His research interests include artificial intelligence in game theory and planning, in particular HTN planning. Dana Nau discovered and elaborated on pathology on certain game trees, where a deeper search does not improve the decision quality, but makes the decision more and more random. Along with Stephen J.J. Smith and Thomas A. Throop, Dana Nau developed AI planning techniques in the Bridge program Bridge Baron.

=Selected Publications=

1979

 * Dana S. Nau (1979). Quality of Decision Versus Depth of Search on Game Trees. Ph.D. thesis, Duke University, advisor Alan Biermann
 * Dana S. Nau (1979). Preliminary results regarding quality of play versus depth of search in game playing. First Internat. Symposium on Policy Analysis and Information Systems

1980 ...

 * Dana S. Nau (1980). Pathology on game trees: A summary of results. AAAI 1980
 * Dana S. Nau (1982). The last player theorem. Artificial Intelligence, Vol. 18
 * Dana S. Nau (1982). An investigation of the causes of pathology in games. Artificial Intelligence, Vol. 19, University of Maryland, College Park, Recommended by Judea Pearl
 * Dana S. Nau, Vipin Kumar, Laveen N. Kanal (1982). A General Paradigm for A.I. Search Procedures. AAAI 1982
 * Dana S. Nau (1983). Decision quality as a function of search depth on game trees. Journal of the ACM, Vol. 30, No. 4
 * Dana S. Nau (1983). On game graph structure and its influence on pathology. International Journal of Computer and Information Sciences, Vol. 12, No, 6
 * Dana S. Nau (1983). Pathology on game trees revisited, and an alternative to minimaxing. Artificial Intelligence, Vol. 21, Nos. 1-2, reprinted in Judea Pearl (ed.) Search and Heuristics. North-Holland
 * Dana S. Nau, Vipin Kumar, Laveen N. Kanal (1984). General Branch and Bound, and its Relation to A* and AO*. Artificial Intelligence, Vol. 23, No. 1
 * Dana S. Nau, Paul W. Purdom, Chun-Hung Tzeng (1986, 2013). An Evaluation of Two Alternatives to Minimax. Machine Intelligence and Pattern Recognition, Vol. 4, arXiv:1304.3445

1990 ...

 * Stephen J.J. Smith, Dana S. Nau, Thomas A. Throop (1992). A hierarchical approach to strategic planning with non-cooperating agents under conditions of uncertainty. Proceedings of the First International Conference on AI Planning Systems
 * Stephen J.J. Smith, Dana S. Nau (1993). Toward an analysis of forward pruning. Technical Report, University of Maryland, College Park
 * Stephen J.J. Smith, Dana S. Nau (1993). Strategic planning for imperfect-information games. Technical Report, University of Maryland, College Park
 * Stephen J.J. Smith, Dana S. Nau (1994). An Analysis of Forward Pruning. AAAI 1994, pdf
 * Stephen J.J. Smith, Dana S. Nau, Thomas A. Throop (1996). A Planning Approach to Declarer Play in Contract Bridge. Computational Intelligence, Vol. 12
 * Stephen J.J. Smith, Dana S. Nau, Thomas A. Throop (1996). Total-Order Multi-Agent Task-Network Planning for Contract Bridge. AAAI 1996
 * Stephen J.J. Smith, Dana S. Nau, Thomas A. Throop (1998). Success in Spades: Using AI Planning Techniques to Win the World Championship of Computer Bridge. AAAI 1998
 * Stephen J.J. Smith, Dana S. Nau, Thomas A. Throop (1998). Computer Bridge: A Big Win for AI Planning. AI Magazine, Vol. 19, No. 2, pdf

2000 ...

 * Mihai Ciocoiu, Dana S. Nau (2000). Ontology-Based Semantics. KR 2000, pdf
 * Malik Ghallab, Dana Nau, Paolo Traverso (2004). Automated Planning: Theory and Practice. Morgan Kaufmann Publishers
 * Austin Parker, Dana S. Nau, V.S. Subrahmanian (2005). Game-Tree Search with Combinatorially Large Belief States. IJCAI 2005, pdf
 * Austin Parker, Dana S. Nau, V.S. Subrahmanian (2006). Overconfidence or Paranoia? Search in Imperfect-Information Games. AAAI 2006, pdf » KriegSpiel
 * Brandon Wilson, Austin Parker, Dana S. Nau (2009). Error Minimizing Minimax: Avoiding Search Pathology in Game Trees. pdf
 * Ryan Carr, Eric Raboin, Austin Parker, Dana S. Nau (2009). Within epsilon of optimal play in the cultaptation social learning game. AAMAS 2009, pdf

2010 ...

 * Dana S. Nau, Mitja Luštrek, Austin Parker, Ivan Bratko, Matjaž Gams (2010). When is it better not to look ahead?. Artificial Intelligence, Vol. 174, No. 16–17, pdf, pdf preprint
 * Brandon Wilson, Inon Zuckerman, Austin Parker, Dana S. Nau (2012). Improving Local Decisions in Adversarial Search. ECAI 2012, pdf
 * Adi Botea, Bruno Bouzy, Michael Buro, Christian Bauckhage, Dana S. Nau (2013). Pathfinding in Games. Artificial and Computational Intelligence in Games 2013, pdf
 * Peter Cowling, Michael Buro, Michal Bída, Adi Botea, Bruno Bouzy, Martin V. Butz, Philip Hingston, Hector Muñoz-Avila, Dana S. Nau, Moshe Sipper (2013). Search in Real-Time Video Games. Artificial and Computational Intelligence in Games 2013, pdf
 * Soham De, Dana S. Nau, Michele J. Gelfand (2016). Using Game Theory to Study the Evolution of Cultural Norms. arXiv:1606.02570
 * Malik Ghallab, Dana Nau, Paolo Traverso (2016). Automated Planning and Acting. Cambridge University Press
 * Soham De, Dana S. Nau, Michele J. Gelfand (2017). Understanding Norm Change: An Evolutionary Game-Theoretic Approach (Extended Version). arXiv:1704.04720
 * Inon Zuckerman, Brandon Wilson, Dana S. Nau (2018). Avoiding game-tree pathology in 2-player adversarial search. Computational Intelligence, Vol. 34, No. 2

=External Links=
 * Dana S. Nau Homepage
 * Dana S. Nau from Wikipedia
 * The Mathematics Genealogy Project - Dana S. Nau
 * Dana S. Nau at Judea Pearl Symposium, 2010, YouTube Video » KriegSpiel, Opponent Model Search

=References= Up one level