Dana Nau

Professor

3241 A.V. Williams Building

(301) 405-2684

Academic Web Page

Education:

Ph.D., Duke University (Computer Science)

Special Awards/Honors:

AAAI Fellow

ACM Fellow

Biography:

Dana Nau is a professor in the Department of Computer Science and the Institute for Systems Research.

His research focuses on artificial intelligence (AI), especially in the areas of game theory and AI planning. Nau also co-directs the Laboratory for Computational Cultural Dynamics.

He is a fellow of AAAI, and has received dozens of other awards and honors.

Some of Nau's best-known accomplishments include (1) discovering game-tree pathology, which has led to subsequent research by dozens of other researchers over the past three decades; (2) co-authoring the strategy-generation algorithm that enabled the Bridge Baron program to win the 1997 world championship of computer bridge; (3) leading the development of the SHOP and SHOP2 automated-planning systems, which have been used in many hundreds of projects in industry, government, and academia; (4) co-authoring a widely used graduate-level textbook, "Automated Planning: Theory and Practice."

He received his doctorate in computer science from Duke University in 1979.

Publications

2011

Sharma P, Khurana U, Shneiderman B, Scharrenbroich M, Locke J. 2011. Speeding Up Network Layout and Centrality Measures for Social Computing Goals. Social Computing, Behavioral-Cultural Modeling and PredictionSocial Computing, Behavioral-Cultural Modeling and Prediction. 6589:244-251.

Ahn J-wook, Taieb-Maimon M, Sopan A, Plaisant C, Shneiderman B. 2011. Temporal Visualization of Social Network Dynamics: Prototypes for Nation of Neighbors. Social Computing, Behavioral-Cultural Modeling and PredictionSocial Computing, Behavioral-Cultural Modeling and Prediction. 6589:309-316.

Cheng K-L, Zuckerman I, Nau DS, Golbeck J. 2011. The Life Game: Cognitive Strategies for Repeated Stochastic Games. :95-102.

Shivashankar V, Jain R, Kuter U, Nau DS. 2011. Real-Time Planning for Covering an Initially-Unknown Spatial Environment.

2010

Raboin E, Nau DS, Kuter U, Gupta SK, Svec P. 2010. Strategy generation in multi-agent imperfect-information pursuit games. :947-954.

Cheng K-L, Zuckerman I, Kuter U, Nau DS. 2010. Emergence of cooperative societies in evolutionary games. :1793-1800.

Roos P, Carr RJ, Nau DS. 2010. Evolution of state-dependent risk preferences. ACM Transactions on Intelligent Systems and Technology (TIST). 1(1):6:1–6:21-6:1–6:21.

Cheng KL, Zuckerman I, Kuter U, Nau DS. 2010. Using a Social Orientation Model for the Evolution of Cooperative Societies. :431-438.

Nau DS, Luštrek M, Parker A, Bratko I, Gams M. 2010. When is it better not to look ahead? Artificial Intelligence. 174(16–17):1323-1338.

2009

Alford R, Kuter U, Nau DS. 2009. Translating HTNs to PDDL: A small amount of domain knowledge can go a long way. :1629-1634.

Au T-C, Kuter U, Nau DS. 2009. Planning for Interactions among Autonomous Agents. Programming Multi-Agent Systems. 5442:1-23.

Kuter U, Nau DS, Pistore M, Traverso P. 2009. Task decomposition on abstract states, for planning under nondeterminism. Artificial Intelligence. 173(5–6):669-695.

Nau DS. 2009. Artificial Intelligence and Automation. Springer Handbook of Automation. :249-268.

Carr R, Raboin E, Parker A, Nau DS. 2009. Within epsilon of optimal play in the cultaptation social learning game. :1327-1328.

2008

Gerevini A, Kuter U, Nau DS, Saetti A, Waisbrot N. 2008. Combining Domain-Independent Planning and HTN Planning: The Duet Planner. :573-577.

Nau DS, Wilkenfeld J. 2008. Computational Cultural Dynamics. Intelligent Systems, IEEE. 23(4):18-19.

Au T-C, Kraus S, Nau DS. 2008. Synthesis of strategies from interaction traces. :855-862.

2007

Kuter U, Nau DS, Reisner E, Goldman R. 2007. Conditionalization: Adapting forward-chaining planners to partially observable environments.

V.S. Subrahmanian, Albanese M, Martinez M?a V, Nau DS, Reforgiato D, Simari GI, Sliva A, Udrea O, Wilkenfeld J. 2007. CARA: A Cultural-Reasoning Architecture. IEEE Intelligent Systems. 22(2):12-16.

Khuller S, Martinez V, Nau DS, Simari G, Sliva A, Subrahmanian V. 2007. Finding most probable worlds of probabilistic logic programs. Scalable Uncertainty Management. :45-59.

Khuller S, Martinez M, Nau DS, Sliva A, Simari G, Subrahmanian V. 2007. Computing most probable worlds of action probabilistic logic programs: scalable estimation for 10^30,000 worlds. Annals of Mathematics and Artificial Intelligence. 51(2):295-331.

Nau DS. 2007. Current Trends in Automated Planning. AI Magazine. 28(4):43-43.

Parker A, Yaman F, Nau DS, V.S. Subrahmanian. 2007. Probabilistic go theories.

Au T-C, Nau DS. 2007. Reactive Query Policies: A Formalism for Planning with Volatile External Information. :243-250.

Khuller S, Martinez V, Nau DS, Simari G, Sliva A, Subrahmanian V. 2007. Finding Most Probable Worlds of Probabilistic Logic Programs. Scalable Uncertainty Management. 4772:45-59.

2006

Au TC, Nau DS. 2006. Accident or intention: That is the question (in the noisy iterated prisoner’s dilemma). :561-568.

Simari G, Sliva A, Nau DS, V.S. Subrahmanian. 2006. A stochastic language for modelling opponent agents. Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems. :244-246.

Au T, Nau DS. 2006. The incompleteness of planning with volatile external information. FRONTIERS IN ARTIFICIAL IN℡LIGENCE AND APPLICATIONS. 141:839-839.

Kuter U, Nau DS. 2006. Controlled search over compact state representations, in nondeterministic planning domains and beyond. 21:1638-1638.

Au TC, Nau DS. 2006. Maintaining cooperation in noisy environments. 21:1561-1561.

Hendler J, Nau DS, Parsia B, Sirin E, Wu D. 2006. Automatic web services composition using Shop2.

Ilghami O, Nau DS, Munoz-Avila H. 2006. Learning to do HTN planning. :390-393.

2005

Ilghami O, Nau DS, Muñoz-Avila H, Aha DW. 2005. Learning preconditions for planning from plan traces and HTN structure. Computational Intelligence. 21(4):388-413.

Yaman F, Nau DS, V.S. Subrahmanian. 2005. Going far, logically. 19:615-615.

Yaman F, Nau DS, V.S. Subrahmanian. 2005. A motion closed world asumption. 19:621-621.

Kuter U, Nau DS, Pistore M, Traverso P. 2005. A hierarchical task-network planner based on symbolic model checking. :300-309.

Nau DS. 2005. Inferencing in Support of Active Templates.

Au T-C, Kuter U, Nau DS. 2005. Web Service Composition with Volatile Information. The Semantic Web – ISWC 2005. 3729:52-66.

Parker A, Nau DS, V.S. Subrahmanian. 2005. Game-tree search with combinatorially large belief states. 19:254-254.

Nau DS, Au T-C, Ilghami O, Kuter U, Wu D, Yaman F, Munoz-Avila H, Murdock JW. 2005. Applications of SHOP and SHOP2. Intelligent Systems, IEEE. 20(2):34-41.

Kuter U, Sirin E, Parsia B, Nau DS, Hendler J. 2005. Information gathering during planning for Web Service composition. Web Semantics: Science, Services and Agents on the World Wide Web. 3(2–3):183-205.

Kuter U, Nau DS. 2005. Using domain-configurable search control for probabilistic planning. 20:1169-1169.

Ilghami O, Muñoz-Avila H, Nau DS, Aha DW. 2005. Learning approximate preconditions for methods in hierarchical plans. :337-344.

2004

Yaman F, Nau DS, V.S. Subrahmanian. 2004. A logic of motion. :85-94.

Au TC, Nau DS, V.S. Subrahmanian. 2004. Utilizing volatile external information during planning. Proceedings of the European Conference on Artificial Intelligence (ECAI). :647-651.

Yaman F, Adali S, Nau DS, Sapino M, Subrahmanian V. 2004. Plan Databases: Model and Algebra. Foundations of Information and Knowledge Systems. 2942:302-319.

Kuter U, Nau DS. 2004. Forward-chaining planning in nondeterministic domains. :513-518.

Sirin E, Parsia B, Wu D, Hendler J, Nau DS. 2004. HTN planning for Web Service composition using SHOP2. Web Semantics: Science, Services and Agents on the World Wide Web. 1(4):377-396.

Kuter U, Sirin E, Nau DS, Parsia B, Hendler J. 2004. Information Gathering During Planning for Web Service Composition. The Semantic Web – ISWC 2004. 3298:335-349.

Ghallab M, Nau DS, Traverso P. 2004. Automated Planning: Theory and Practice.

2003

Yao Z, Gupta SK, Nau DS. 2003. Algorithms for selecting cutters in multi-part milling problems. Computer-Aided Design. 35(9):825-839.

Wu D, Parsia B, Sirin E, Hendler J, Nau DS. 2003. Automating DAML-S Web Services Composition Using SHOP2. The Semantic Web - ISWC 2003. 2870:195-210.

Dix J, Kuter U, Nau DS. 2003. Planning in Answer Set Programming Using Ordered Task Decomposition. KI 2003: Advances in Artificial Intelligence. 2821:490-504.

Nau DS, Au TC, Ilghami O, Kuter U, Murdock JW, Wu D, Yaman F. 2003. SHOP2: An HTN planning system. J. Artif. Intell. Res. (JAIR). 20:379-404.

Dix J, Muñoz-Avila H, Nau DS, Zhang L. 2003. IMPACTing SHOP: Putting an AI Planner Into a Multi-Agent Environment. Annals of Mathematics and Artificial Intelligence. 37(4):381-407.

Ilghami O, Nau DS. 2003. A General Approach to Synthesize Problem-Specific Planners.

2002

Wu D, Nau DS. 2002. M-Translog-2: A Planning Domain Designed for AIPS-2002. UMIACS-TR-2002-82

Au T-C, Muñoz-Avila H, Nau DS. 2002. On the Complexity of Plan Adaptation by Derivational Analogy in a Universal Classical Planning Framework. Advances in Case-Based Reasoning. 2416:199-206.

Dix J, Muñoz-Avila H, Nau DS, Zhang L. 2002. Planning in a multi-agent environment: theory and practice. :944-945.

Dix J, Kuter U, Nau DS. 2002. HTN Planning in Answer Set Programming. UMIACS-TR-2002-18

Ilghami O, Nau DS, Munoz-Avila H, Aha DW. 2002. CaMeL: Learning method preconditions for HTN planning. :131-14.

Dix J, Munoz-Avila H, Nau DS, Zhang L. 2002. Theoretical and Empirical Aspects of a Planner in a Multi-agent Environment. Logics in Artificial Intelligence. 2424:173-185.

2001

Yao Z, Gupta SK, Nau DS. 2001. A geometric algorithm for selecting optimal set of cutters for multi-part milling. :130-139.

2000

Yao Z, Gupta SK, Nau DS. 2000. Selecting Flat End Mills for 2-1/2D Milling Operations. ISR; TR 2000-41

Yao Z, Gupta SK, Nau DS. 2000. Finding the maximal cutter for 2-D milling operations. :10-13.

Yao Z, Gupta SK, Nau DS. 2000. A geometric algorithm for finding the maximal cutter for 2-D milling operations. :26-28.

Yao Z, Gupta SK, Nau DS. 2000. A Geometric Algorithm for Finding the Largest Milling Cutter. ISR; TR 2000-40

Yao Z, Gupta SK, Nau DS. 2000. A Geometric Algorithm for Multi-Part Milling Cutter Selection. ISR; TR 2000-42

1998

Gupta SK, Nau DS, Regli WC. 1998. IMACS: a case study in real-world planning. Intelligent Systems and their Applications, IEEE. 13(3):49-60.

Regli WC, Gupta SK, Nau DS. 1998. Feature Recognition for Interactive Applications: Exploiting Distributed Resources. UMIACS-TR-94-126.1