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Note: Links lead to the DBLP on the Web. Adele E. Howe Jean-Paul Watson , Adele E. Howe, L. Darrell Whitley : Deconstructing Nowicki and Smutnicki's i -TSAB tabu search algorithm for the job-shop scheduling problem. Computers & OR 33 : 2623-2644 (2006) Elizabeth Sugar Boese , Adele E. Howe: Genre Classification of Web Documents. AAAI 2005 : 1596-1597 Elizabeth Sugar Boese , Adele E. Howe: Effects of web document evolution on genre classification. CIKM 2005 : 632-639 Laura Barbulescu , L. Darrell Whitley , Adele E. Howe: Leap Before You Look: An Effective Strategy in an Oversubscribed Scheduling Problem. AAAI 2004 : 143-148 Gabriel Somlo , Adele E. Howe: QueryTracker: An Agent for Tracking Persistent Information Needs. AAMAS 2004 : 488-495 Laura Barbulescu , Adele E. Howe, L. Darrell Whitley , Mark Roberts : Trading Places: How to Schedule More in a Multi-Resource Oversubscribed Scheduling Problem. ICAPS 2004 : 227-234 Gabriel Somlo , Adele E. Howe: Filtering for personal web information agents. SIGIR 2004 : 588-589 Laura Barbulescu , Jean-Paul Watson , L. Darrell Whitley , Adele E. Howe: Scheduling Space-Ground Communications for the Air Force Satellite Control Network. J. Scheduling 7 (1): 7-34 (2004) Gabriel Somlo , Adele E. Howe: Using web helper agent profiles in query generation. AAMAS 2003 : 812-818 Jean-Paul Watson , J. Christopher Beck , Adele E. Howe, L. Darrell Whitley : Problem difficulty for tabu search in job-shop scheduling. Artif. Intell. 143 (2): 189-217 (2003) Laura Barbulescu , Adele E. Howe, Jean-Paul Watson , L. Darrell Whitley : Satellite Range Scheduling: A Comparison of Genetic, Heuristic and Local Search. PPSN 2002 : 611-620 Jean-Paul Watson , Laura Barbulescu , L. Darrell Whitley , Adele E. Howe: Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance. INFORMS Journal on Computing 14 (2): 98-123 (2002) Adele E. Howe, Eric Dahlman : A Critical Assessment of Benchmark Comparison in Planning. J. Artif. Intell. Res. (JAIR) 17 : 1-3 (2002) Anneliese Amschler Andrews , Chunhui Zhu , Michael Scheetz , Eric Dahlman , Adele E. Howe: AI Planner Assisted Test Generation. Software Quality Journal 10 (3): 225-259 (2002) Gabriel Somlo , Adele E. Howe: Incremental clustering for profile maintenance in information gathering web agents. Agents 2001 : 262-269 Gabriel Somlo , Adele E. Howe: Adaptive Lightweight Text Filtering. IDA 2001 : 319-329 Anneliese von Mayrhauser , Michael Scheetz , Eric Dahlman , Adele E. Howe: Planner Based Error Recovery Testing. ISSRE 2000 : 186-197 Larry D. Pyeatt , Adele E. Howe: Evaluating robustness in a two layer simulated robot architecture. J. Exp. Theor. Artif. Intell. 12 (2): 213-234 (2000) Jean-Paul Watson , Laura Barbulescu , Adele E. Howe, L. Darrell Whitley : Algorithm Performance and Problem Structure for Flow-shop Scheduling. AAAI/IAAI 1999 : 688-695 Larry D. Pyeatt , Adele E. Howe: Integrating POMDP and Reinforcement Learning for a Two Layer Simulated Robot Architecture. Agents 1999 : 168-174 Adele E. Howe, Eric Dahlman , Christoper Hansen , Michael Scheetz , Anneliese von Mayrhauser : Exploiting Competitive Planner Performance. ECP 1999 : 62-72 Larry D. Pyeatt , Adele E. Howe: A Parallel Algorithm for POMDP Solution. ECP 1999 : 73-83 Larry D. Pyeatt , Adele E. Howe: Learning to Race: Experiments with a Simulated Race Car. FLAIRS Conference 1998 : 357-361 Jean-Paul Watson , Charlie Ross , V. Eisele , J. Denton , José Bins , C. Guerra , L. Darrell Whitley , Adele E. Howe: The Traveling Salesrep Problem, Edge Assembly Crossover, and 2-opt. PPSN 1998 : 823-834 Adele E. Howe, Gabriel Somlo : Modeling Intelligent System Execution as State Transition Diagrams to Support Debugging. AADEBUG 1997 : 79-86 Adele E. Howe, Gabriel Somlo : Modelling Discrete Event Sequences as State Transition Diagrams. IDA 1997 : 573-584 Daniel Dreilinger , Adele E. Howe: Experiences with Selecting Search Engines Using Metasearch. ACM Trans. Inf. Syst. 15 (3): 195-222 (1997) Adele E. Howe, Daniel Dreilinger : SAVVYSEARCH: A Metasearch Engine That Learns Which Search Engines to Query. AI Magazine 18 (2): 19-25 (1997) Adele E. Howe, Anneliese von Mayrhauser , Richard T. Mraz : Test Case Generation as an AI Planning Problem. Autom. Softw. Eng. 4 (1): 77-106 (1997) Soraya B. Rana , Adele E. Howe, L. Darrell Whitley , Keith E. Mathias : Comparing Heuristic, Evolutionary and Local Search Approaches to Scheduling. AIPS 1996 : 174-181 Raghavan Srinivasan , Adele E. Howe: Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner. IJCAI 1995 : 1620-1626 Adele E. Howe, Anneliese von Mayrhauser , Richard T. Mraz : Test Sequences as Plans: An Experiment in Using an AI Planner to Generate System Tests. KBSE 1995 : 184-191 Adele E. Howe, Paul R. Cohen : Understanding Planner Behavior. Artif. Intell. 76 (1-2): 125-166 (1995) Adele E. Howe: Improving the Reliability of Artificial Intelligence Planning Systems by Analyzing their Failure Recovery. IEEE Trans. Knowl. Data Eng. 7 (1): 14-25 (1995) Adele E. Howe, Robert St. Amant , Paul R. Cohen : Integrating Statistical Methods for Characterizing Causal Influences on Planner Behavior over Time. ICTAI 1994 : 56-62 Adele E. Howe, Aaron D. Fuegi : Methods for Finding Influences on Program Failure. ICTAI 1994 : 764-767 Adele E. Howe: Analyzing Failure Recovery to Improve Planner Design. AAAI 1992 : 387-392 Adele E. Howe, Paul R. Cohen : Failure Recovery: A Model and Experiments. AAAI 1991 : 801-808 Adele E. Howe, David M. Hart , Paul R. Cohen : Addressing Real-Time Constraints in the Design of Autonomous Agents. Real-Time Systems 2 (1-2): 81-96 (1990) Paul R. Cohen , Michael L. Greenberg , David M. Hart , Adele E. Howe: Trial by Fire: Understanding the Design Requirements for Agents in Complex Environments. AI Magazine 10 (3): 32-48 (1989) Paul R. Cohen , Adele E. Howe: How Evaluation Guides AI Research: The Message Still Counts More than the Medium. AI Magazine 9 (4): 35-43 (1988) Adele E. Howe, Paul R. Cohen , John R. Dixon , Melvin K. Simmons : Dominic: A Domain-Independent Program for Mechanical Engineering Design. AI in Engineering 1 (1): 23-28 (1986) 1 [ 8 ] 2 [ 11 ] [ 14 ] [ 22 ] [ 26 ] [ 29 ] 3 [ 24 ] [ 31 ] [ 32 ] [ 35 ] [ 37 ] [ 39 ] 4 [ 33 ] 5 [ 19 ] 6 [ 40 ] [ 41 ] 7 [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 8 ] [ 10 ] 8 [ 22 ] [ 26 ] [ 29 ] [ 30 ] 9 [ 19 ] 10 [ 1 ] 11 [ 15 ] [ 16 ] 12 [ 19 ] 13 [ 7 ] 14 [ 3 ] 15 [ 19 ] 16 [ 22 ] 17 [ 3 ] [ 4 ] 18 [ 13 ] 19 [ 11 ] [ 14 ] 20 [ 20 ] [ 21 ] [ 23 ] [ 25 ] 21 [ 13 ] 22 [ 37 ] 23 [ 19 ] 24 [ 22 ] [ 26 ] [ 29 ] 25 [ 1 ] 26 [ 17 ] [ 18 ] [ 27 ] [ 28 ] [ 34 ] [ 36 ] [ 38 ] 27 [ 12 ] 28 [ 19 ] [ 24 ] [ 31 ] [ 32 ] [ 33 ] [ 35 ] [ 42 ] 29 [ 13 ] [ 19 ] [ 24 ] [ 31 ] [ 32 ] [ 33 ] [ 35 ] [ 37 ] [ 39 ] [ 42 ] 30 [ 29 ]  ©2006 Association for Computing Machinery |
