Ruml, Wheeler - Department of Computer Science, University of New Hampshire

• Heuristic Search in Bounded-depth Trees: Best-Leaf-First Search
• Suboptimal and Anytime Heuristic Search on Multi-Core Machines Ethan Burns and Seth Lemons and Wheeler Ruml
• Best-First Heuristic Search for Multi-Core Machines Ethan Burns1
• The Joy of Forgetting: Faster Anytime Search via Restarting Silvia Richter
• Heuristic Search in Bounded-depth Trees: Best-Leaf-First Search Wheeler Ruml
• Finding Acceptable Solutions Faster Using Inadmissible Information Jordan Thayer and Wheeler Ruml
• A Simple Testbed for On-line Planning Dept. of Computer Science and Engineering
• David M. Bond Niels A. Widger
• Wheeler Ruml (UNH) Job Hunting 1 / 17 Job Hunting in Industry and Academia
• On-line Planning and Scheduling for High-speed Manufacturing Wheeler Ruml and Minh B. Do and Markus P. J. Fromherz
• Ethan Burns (UNH) Abstraction in Multicore Heuristic Search 1 / 31 Parallel Best-First Search: The Role of Abstraction
• Ethan Burns (UNH) Heuristic Search for Multi-core 1 / 38 Suboptimal and Anytime Heuristic Search
• Planning for Modular Printers: Beyond Productivity Embedded Reasoning Area
• orssnotursvtwns uopnpuspturs
• Using Distance Estimates in Heuristic Search Jordan T. Thayer and Wheeler Ruml
• The Logic of Benchmarking: A Case Against State-of-the-Art Performance Wheeler Ruml
• Using Distance Estimates in Heuristic Search: A Re-evaluation Jordan T. Thayer and Wheeler Ruml and Jeff Kreis
• UNCORRECTEDPROOF 2 Positioning using local maps q
• Faster Than Weighted A*: An Optimistic Approach to Bounded Suboptimal Search
• A Comparison of Greedy Search Algorithms Christopher Wilt and Jordan Thayer and Wheeler Ruml
• Heuristic Search for Large Problems With Real Costs Matthew Hatem and Ethan Burns and Wheeler Ruml
• Bounded Suboptimal Search: A Direct Approach Using Inadmissible Estimates Jordan T. Thayer and Wheeler Ruml
• Jordan Thayer (UNH) Bounded Suboptimal Search 1 / 18 Finding Acceptable Solutions Faster
• Parallel Best-First Search: Optimal and Suboptimal Solutions Ethan Burns1
• Seth Lemons (UNH) Parallel Best-First Search: Optimal and Suboptimal Solutions 1 / 39 Parallel Best-First Search: Optimal and Suboptimal Solutions
• Anytime Heuristic Search: Frameworks and Algorithms Jordan Thayer and Wheeler Ruml
• Searching Without a Heuristic: Efficient Use of Abstraction Bradford Larsen, Ethan Burns, Wheeler Ruml
• Searching Without a Heuristic: Efficient Use of Abstraction
• The Joy of Forgetting: Faster Anytime Search via Restarting Silvia Richter
• Ethan Burns (UNH) Heuristic Search for Multi-Core 1 / 25 Best-First Heuristic Search for Multi-Core Machines
• To appear in the Notes of the IJCAI-01 Workshop on Stochastic Search. Stochastic Tree Search: Where to Put the Randomness?
• To appear in the Proceedings of IJCAI-01. Incomplete Tree Search using Adaptive Probing
• Improving Determinization in Hindsight for On-line Probabilistic Planning Embedded Reasoning Area
• Continual On-line Planning as Decision-Theoretic Incremental Heuristic Search Seth Lemons1
• Lessons Learned in Applying Domain-Independent Planning to High-Speed Manufacturing
• Assigning Features using Additive Clustering Wheeler Ruml
• Jordan Thayer and Wheeler Ruml and Jeff Kreis Using Distance Estimates in Search:ARe-evaluation
• Cognitive Neuropsychology Copyright c 2003 by the authors. Interactivity and Continuity in
• Learning Inadmissible Heuristics During Search Jordan T. Thayer and Austin Dionne and Wheeler Ruml
• Localization from Connectivity in Sensor Networks
• Real-Time Search in Dynamic Worlds David M. Bond, Niels A. Widger, Wheeler Ruml
• Parallel Best-First Search: The Role of Abstraction Ethan Burns and Sofia Lemons and Wheeler Ruml
• Constructing Distributed Representations Using Additive Clustering
• Fast and Loose in Bounded Suboptimal Heuristic Search Jordan T. Thayer and Wheeler Ruml
• Introduction Experiments in Planning
• Wheeler Ruml (UNH) Against State-of-the-Art Performance 1 / 9 The Logic of Benchmarking
• On-line Planning and Scheduling: An Application to Controlling Modular Printers
• * dave.biegelsen@parc.com; phone 1 650 812 4137 Integrated Parallel Printing Systems with Hypermodular Architecture
• Using Prior Knowledge with Adaptive Probing Wheeler Ruml
• Deadline-Aware Search Using On-line Measures of Behavior Austin J. Dionne and Jordan T. Thayer and Wheeler Ruml
• Jordan Thayer (UNH) Learning During Search 1 / 20 Learning Inadmissible Heuristics During Search
• Wheeler Ruml (UNH) Search Algorithms as Agents 1 / 40 Search Algorithms as Agents
• HEURISTIC SEARCH UNDER A DEADLINE Austin Dionne
• Jordan Thayer and Wheeler Ruml (UNH) Distance Estimates For Search 1 / 40 Using Distance Estimates In Heuristic Search
• Incomplete Tree Search using Adaptive Probing Wheeler Ruml
• Best-first Search for Bounded-depth Trees Kevin Rose and Ethan Burns and Wheeler Ruml
• Selecting a Greedy Search Algorithm Technical Report 10-07
• Jordan T. Thayer (UNH) Bounded Suboptimal Search 1 / 19 Bounded Suboptimal Search
• Jordan Thayer and Wheeler Ruml (UNH) Suboptimal Search 1 / 28 A Survey of Suboptimal Search Algorithms
• Finding Acceptable Solutions Faster Using Inadmissible Information
• Cost-Based Heuristic Search is Sensitive to the Ratio of Operator Costs Christopher Wilt and Wheeler Ruml
• Wheeler Ruml (UNH) When Optimal Just Isn't Good Enough 1 / 33 Planning Algorithms
• Matthew Hatem (UNH) Heuristic Search for Large Problems with Real Costs 1 / 31 Heuristic Search for Large Problems with Real Costs
• Ethan Burns (UNH) Iterative-deepening Search with On-line Tree Size Prediction 1 / 30 Iterative-deepening Search with On-line Tree Size Prediction
• Iterative-Deepening Search with On-line Tree Size Prediction