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Dana S. Nau ^[1]

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 ^[2] .

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

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

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

Mihai Ciocoiu, Dana S. Nau (2000). Ontology-Based Semantics. KR 2000, pdf ^[6]
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