2021

• Necessary and Sufficient Conditions for Avoiding Reopenings in Best First Suboptimal Search with General Bounding Functions,
  Jingwei Chen and Nathan R. Sturtevant,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Jump Point Search with Temporal Obstacles,
  Shuli Hu, Daniel Harabor, Graeme Gange, Peter Stuckey and Nathan R. Sturtevant,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [abstract] [pdf] [.bib]

• Iterative-deepening Bidirectional Heuristic Search with Restricted Memory,
  Shahaf Shperberg, Steven Danishevski, Ariel Felner and Nathan R. Sturtevant,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [.bib]

• Conflict-Based Increasing Cost Search,
  Thayne T. Walker, Nathan R. Sturtevant, Han Zhang, Jiaoyang Li, Ariel Felner and T. K. Satish Kumar,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [.bib]

• The Impact of Visualizing Design Gradients for Human Designers,
  Matthew Guzdial, Nathan R. Sturtevant and Carolyn Yang,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [.bib]

• The Definition-Context-Purpose Paradigm and Other Insights Learned from Industry Professionals About the Definition of a Quest,
  Kristen Yu, Matthew Guzdial and Nathan R. Sturtevant,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [.bib]

• Towards Disambiguating Quests as a Technical Term,
  Kristen K. Yu, Matthew Guzdial and Nathan R. Sturtevant,
  Proceedings of the Sixteenth International Conference on the Foundations of Digital Games (FDG)
  [abstract] [pdf] [video] [.bib]

  Short Papers, Workshops, Others

  • Avoiding Re-expansions in Suboptimal Best-First Search,
    Jingwei Chen and Nathan R. Sturtevant,
    Symposium on Combinatorial Search (SoCS)
    [abstract] [pdf] [demo] [.bib]

  • Demos for a Course in Single-Agent Heuristic Search,
    Nathan R. Sturtevant,
    International Conference on Automated Planning and Scheduling (ICAPS)
    [abstract] [pdf] [.bib]

  • Measuring the Solution Strength of Learning Agents in Adversarial Perfect Information Games,
    Zaheen Farraz Ahmad, Nathan Sturtevant and Michael Bowling,
    AAAI-21 Workshop on Reinforcement Learning in Games
    [abstract] [pdf] [.bib]

2020

• Multi-Directional Heuristic Search,
  Dor Atzmon, Jiaoyang Li, Ariel Felner, Eliran Nachmani, Shahaf Shperberg, Nathan Sturtevant and Sven Koenig,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Probabilistic Robust Multi-Agent Path Finding,
  Dor Atzmon, Roni Stern, Ariel Felner, Nathan Sturtevant and Sven Koenig,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [abstract] [pdf] [.bib]

• Predicting the Effectiveness of Bidirectional Heuristic Search,
  Nathan R. Sturtevant, Shahaf Shperberg, Ariel Felner and Jingwei Chen,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [abstract] [pdf] [slides] [poster] [.bib]

• Generalized and Sub-Optimal Bipartite Constraints for Conflict-Based Search,
  Thayne Walker, Nathan R Sturtevant and Ariel Felner,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• A Guide to Budgeted Tree Search,
  Nathan Sturtevant and Malte Helmert,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [video] [slides] [demo] [.bib]

• The Unexpected Consequence of Incremental Design Changes,
  Nathan R. Sturtevant, Nicolas Decroocq, Aaron Tripodi and Matthew Guzdial,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [video] [slides] [.bib]

  Short Papers, Workshops, Others

  • A Demonstration of Anhinga: A Mixed-Initiative EPCG Tool for Snakebird,
    Nathan R. Sturtevant, Nicolas Decroocq, Aaron Tripodi, Carolyn Yang and Matthew Guzdial,
    Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
    [abstract] [pdf] [.bib]

  • What is a Quest?,
    Kristen Yu, Nathan R. Sturtevant and Matthew Guzdial,
    Intelligent Narrative Technolgies Workshop
    [abstract] [pdf] [.bib]

  • Abstraction and Refinement in Games with Dynamic Weighted Terrain,
    Nathan R. Sturtevant, Devon Sigurdson, Bjorn Taylor and Tim Gibson,
    AAAI Conference on Artificial Intelligence, Sister Conference Track
    [abstract] [pdf] [.bib]

2019

• Conditions for Avoiding Node Re-expansions in Bounded Suboptimal Search,
  Jingwei Chen and Nathan R. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [demo] [.bib]

• Iterative Budgeted Exponential Search,
  Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau and Nathan R. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [slides] [demo] [.bib]

• Direction-Optimizing Breadth-First Search with External Memory Storage,
  Shuli Hu and Nathan R. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Enriching Non-parametric Bidirectional Search Algorithms,
  Shahaf Shperberg, Ariel Felner, Nathan R Sturtevant, Avi Hayoun and Eyal S Shimony,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Revisiting Suboptimal Search,
  Jingwei Chen, Nathan R. Sturtevant, William Doyle and Wheeler Ruml,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [demo] [.bib]

• Policy Based Inference in Trick-Taking Card Games,
  Douglas Rebstock, Chris Solinas, Michael Buro and Nathan R. Sturtevant,
  IEEE Conference on Games
  [abstract] [pdf] [.bib]

• Improving Bidirectional Heuristic Search by Bound Propagation,
  Shahaf S. Shperberg, Ariel Felner, Nathan R. Sturtevant, Solomon Eyal Shimony and Avi Hayoun,
  Symposium on Combinatorial Search (SoCS)
  Note: Won SoCS 2019 best paper / best student paper award
  [abstract] [pdf] [.bib]

• Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks,
  Roni Stern, Nathan R. Sturtevant, Ariel Felner, Sven Koenig, Hang Ma, Thayne T. Walker, Jiaoyang Li, Dor Atzmon, Liron Cohen, T. K. Satish Kumar, Eli Boyarski and Roman Bartak,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• On Strongly Solving Chinese Checkers,
  Nathan R. Sturtevant,
  Advances in Computer Games (ACG)
  Note: The 6x6 results in Table 1 have now been verified with a different solver.
  [abstract] [pdf] [.bib]

• Pathfinding and Abstraction with Dynamic Terrain Costs,
  Nathan R. Sturtevant, Devon Sigurdson, Bjorn Taylor and Tim Gibson,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [demo] [.bib]

• Application of Retrograde Analysis on Fighting Games,
  Kristen Yu and Nathan R. Sturtevant,
  IEEE Conference on Games
  [abstract] [pdf] [.bib]

  Short Papers, Workshops, Others

  • Unbounded Sub-Optimal Conflict-Based Search in Complex Domains,
    Thayne T. Walker, Nathan R. Sturtevant and Ariel Felner,
    Symposium on Combinatorial Search (SoCS)
    [pdf] [.bib]

  • Exploring EPCG in The Witness,
    Nathan R. Sturtevant,
    Knowledge Extraction from Games (AAAI workshop)
    [abstract] [pdf] [slides] [.bib]

2018

• A Brief History and Recent Achievements in Bidirectional Search,
  Nathan R. Sturtevant and Ariel Felner,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [slides] [.bib]

• Extended Increasing Cost Tree Search for Non-Unit Cost Domains,
  Thayne Walker, Nathan R. Sturtevant and Ariel Felner,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Minimizing Node Expansions in Bidirectional Search with Consistent Heuristics,
  Eshed Shaham, Ariel Felner, Nathan R. Sturtevant and Jeffrey S. Rosenschein,
  Symposium on Combinatorial Search (SoCS)
  Note: Won SoCS 2018 Best Student Paper award
  [abstract] [pdf] [.bib]

• Algorithms for Exhaustive and Semi-Exhaustive Procedural Content Generation,
  Nathan R. Sturtevant and Matheus Jun Ota,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [slides] [.bib]

  Short Papers, Workshops, Others

  • Benchmarks for Pathfinding in 3D Voxel Space,
    Daniel Brewer and Nathan R. Sturtevant,
    Symposium on Combinatorial Search (SoCS)
    [abstract] [pdf] [slides] [.bib]

  • Rapid Randomized Restarts for Multi-Agent Path Finding,
    Liron Cohen, Glenn Wagner, David Chan, Howie Choset, Nathan Sturtevant, T. K. Satish Kumar and Sven Koenig,
    Symposium on Combinatorial Search (SoCS)
    [abstract] [.bib]

  • Rapid Randomized Restarts for Multi-Agent Path Finding: Preliminary Results,
    Liron Cohen, Sven Koenig, T. K. Satish Kumar, Glenn Wagner, Howie Choset, David Chan and Nathan Sturtevant,
    Autonomous Agents and Multiagent Systems (AAMAS)
    [abstract] [pdf] [.bib]

  • AI Education Matters: Teaching Search Algorithms,
    Nathan R. Sturtevant,
    AI Matters
    [pdf] [.bib]

2017

• MM: A Bidirectional Search That Is Guaranteed to Meet in the Middle,
  Robert C. Holte, Ariel Felner, Guni Sharon, Nathan R. Sturtevant and Jingwei Chen,
  Artificial Intelligence (AIJ)
  [abstract] [pdf] [.bib]

• Front-to-End Bidirectional Heuristic Search with Near-Optimal Node Expansions,
  Jingwei Chen, Robert C. Holte, Sandra Zilles and Nathan R. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [poster] [.bib]

• Sufficient Conditions for Node Expansion in Bidirectional Heuristic Search,
  Jurgen Eckerle, Jingwei Chen, Nathan Sturtevant, Sandra Zilles and Robert Holte,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [abstract] [pdf] [slides] [.bib]

• Value Compression of Pattern Databases,
  Nathan R. Sturtevant, Ariel Felner and Malte Helmert,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding,
  Thayne T. Walker, David Chan and Nathan R. Sturtevant,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [abstract] [pdf] [.bib]

• The Minimal Set of States that Must be Expanded in a Front-to-end Bidirectional Search,
  Eshed Shaham, Ariel Felner, Jingwei Chen and Nathan R. Sturtevant,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• Faster A* with Goal Bounding,
  Steve Rabin and Nathan R. Sturtevant,
  Game AI Pro 3: Collected Wisdom of Game AI Professionals
  [.bib]

• Faster Dijkstra Search on Uniform Cost Grids,
  Nathan R. Sturtevant and Steve Rabin,
  Game AI Pro 3: Collected Wisdom of Game AI Professionals
  [.bib]

  Short Papers, Workshops, Others

  • On Variable Dependencies and Compressed Pattern Databases,
    Malte Helmert, Nathan R. Sturtevant and Ariel Felner,
    Symposium on Combinatorial Search (SoCS)
    [abstract] [pdf] [slides] [.bib]

  • A Study of Forward Versus Backwards Endgame Solvers with Results in Chinese Checkers,
    Nathan R. Sturtevant and Abdallah Saffidine,
    Computer Game Workshop at IJCAI
    [abstract] [pdf] [.bib]

2016

• Scrubbing During Learning in Real-Time Heuristic Search,
  Nathan R. Sturtevant and Vadim Bulitko,
  Journal of Artificial Intelligence Research (JAIR)
  [.bib]

• Bidirectional Search That Is Guaranteed to Meet in the Middle,
  Robert C. Holte, Ariel Felner, Guni Sharon and Nathan R. Sturtevant,
  AAAI Conference on Artificial Intelligence
  Note: Received AAAI 2016 Distinguished Paper Award
  [abstract] [pdf] [.bib]

• Combining Bounding Boxes and JPS to Prune Grid Pathfinding,
  Steve Rabin and Nathan R. Sturtevant,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [poster] [.bib]

• Canonical Orderings on Grids,
  Nathan R. Sturtevant and Steve Rabin,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [slides] [poster] [.bib]

• External Memory Bidirectional Search,
  Nathan Sturtevant and Jingwei Chen,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [slides] [poster] [.bib]

  Short Papers, Workshops, Others

  • Extended Abstract: An Improved Priority Function for Bidirectional Heuristic Search,
    Guni Sharon, Robert C. Holte, Ariel Felner and Nathan R. Sturtevant,
    Symposium on Combinatorial Search (SoCS)
    [.bib]

  • Generalizing JPS Symmetry Detection: Canonical Orderings on Graphs,
    Nathan R. Sturtevant,
    Symposium on Combinatorial Search (SoCS)
    [abstract] [pdf] [slides] [.bib]

  • Deep Static and Dynamic Level Analysis: A Study on Infinite Mario,
    Matthew Guzdial, Nathan Sturtevant and Boyang Li,
    Experimental AI in Games (AIIDE Workshop)
    [pdf] [.bib]

2015

• Conflict-based Search for Optimal Multi-agent Pathfinding,
  Guni Sharon, Roni Stern, Ariel Felner and Nathan R. Sturtevant,
  Artificial Intelligence (AIJ)
  Note: Received 2020 AIJ Prominent Paper Award
  [abstract] [pdf] [.bib]

• The Grid-Based Path Planning Competition: 2014 Entries and Results,
  Nathan R Sturtevant, Jason Traish, James Tulip, Tansel Uras, Sven Koenig, Ben Strasser, Adi Botea, Daniel Harabor and Steve Rabin,
  Eighth Annual Symposium on Combinatorial Search
  [abstract] [pdf] [.bib]

• An Introduction to Search for Games,
  Nathan Sturtevant,
  Game AI Pro 2: Collected Wisdom of Game AI Professionals
  [.bib]

• Monte-Carlo Tree Search and Related Algorithms for Games,
  Nathan Sturtevant,
  Game AI Pro 2: Collected Wisdom of Game AI Professionals
  [.bib]

  Short Papers, Workshops, Others

  • Challenges and Progress on Using Large Lossy Endgame Databases in Chinese Checkers,
    Nathan Sturtevant,
    IJCAI Workshop on Computer Games
    [abstract] [.bib]

2014

• Enhanced Partial Expansion A*,
  M. Goldenberg, A. Felner, R. Stern, G. Sharon, N. Sturtevant, R. C. Holte and J. Schaeffer,
  Journal of Artificial Intelligence Research (JAIR)
  [abstract] [pdf] [.bib]

• Exponential Deepening A* for Real-Time Agent-Centered Search,
  Guni Sharon, Ariel Felner and Nathan Sturtevant,
  AAAI Conference on Artificial Intelligence
  [abstract] [.bib]

• Worst-Case Solution Quality Analysis When Not Re-Expanding Nodes in Best-First Search,
  Richard Valenzano, Nathan Sturtevant and Jonathan Schaeffer,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Monte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups,
  Marc Lanctot, Mark H. M. Winands, Tom Pepels and Nathan R. Sturtevant,
  Computational Intelligence in Games (CIG)
  [abstract] [pdf] [.bib]

• Estimating the Size of Heuristic Search Expanded Graphs,
  Levis Lelis, Roni Stern and Nathan Sturtevant,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• Exploiting the Rubik's Cube 12-edge PDB by Combining Partial Pattern Databases and Bloom Filters,
  Nathan Sturtevant, Ariel Felner and Malte Helmert,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• Reaching the Goal in Real-Time Heuristic Search: Scrubbing Behavior is Unavoidable,
  Nathan Sturtevant and Vadim Bulitko,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

  Short Papers, Workshops, Others

  • ArvandHerd 2014,
    R. Valenzano, H. Nakhost, M. Muller, J. Schaeffer and N. Sturtevant,
    Proc. 8th International Planning Competition (IPC 2014)
    [abstract] [pdf] [.bib]

  • A Comparison of Knowledge-Based GBFS Enhancements and Knowledge-Free Exploration (Short Paper),
    Richard Valenzano, Nathan Sturtevant, Jonathan Schaeffer and Fan Xie,
    International Conference on Automated Planning and Scheduling (ICAPS)
    [abstract] [pdf] [.bib]

  • The Grid-Based Path-Planning Competition,
    Nathan R. Sturtevant,
    AI Magazine
    [abstract] [.bib]

  • Playable Experiences at AIIDE 2014,
    Nathan R. Sturtevant, Jeff Orkin, Robert Zubek, Michael Cook, Stephen G. Ware, Christian Stith, R. Michael Young, Phillip Wright, Squirrel Eiserloh, Alejandro Ramirez-Sanabria, Vadim Bulitko and Kieran Lord,
    Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
    [abstract] [pdf] [.bib]

2013

• Subset Selection of Search Heuristics,
  Chris Rayner, Nathan Sturtevant and Michael Bowling,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Minimizing Writes in Parallel External Memory Search,
  N.R. Sturtevant and M.J. Rutherford,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [poster] [.bib]

• A Parameterized Family of Equilibrium Profiles for Three-Player Kuhn Poker,
  Duane Szafron, Richard Gibson and Nathan Sturtevant,
  Autonomous Agents and Multiagent Systems (AAMAS)
  [abstract] [pdf] [.bib]

• Using Alternative Suboptimality Bounds in Heuristic Search,
  Richard Valenzano, Shahab Jabbari Arfaee, Roni Stern, Jordan Thayer and Nathan Sturtevant,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [abstract] [pdf] [.bib]

• Optimal-Generation Variants of EPEA*,
  Meir Goldenberg, Ariel Felner, Nathan Sturtevant, Robert C. Holte and Jonathan Schaeffer,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• Online Detection of Dead States in Real-Time Agent-Centered Search,
  Guni Sharon, Nathan Sturtevant and Ariel Felner,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• Incorporating Human Relationships Into Path Planning,
  N.R. Sturtevant,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [poster] [.bib]

• External Memory PDBs: Initial Results,
  Nathan Sturtevant,
  Symposium on Abstraction, Reformulation and Approximation (SARA)
  [abstract] [pdf] [.bib]

• Pathfinding Architecture Optimizations,
  Steve Rabin and Nathan Sturtevant,
  Game AI Pro: Collected Wisdom of Game AI Professionals
  [.bib]

• Choosing a Search Space Representation,
  Nathan R. Sturtevant,
  Game AI Pro: Collected Wisdom of Game AI Professionals
  [.bib]

  Short Papers, Workshops, Others

  • Finding Bounded Suboptimal Multi-Agent Path Planning Solutions Using Increasing Cost Tree Search (Extended Abstract),
    Faten Aljaloud and Nathan Sturtevant,
    Symposium on Combinatorial Search (SoCS)
    [abstract] [pdf] [.bib]

  • UCT Enhancements in Chinese Checkers Using an Endgame Database,
    Max Roschke and Nathan Sturtevant,
    IJCAI Workshop on Computer Games
    [abstract] [pdf] [.bib]

  • An Argument for Large-Scale Breadth-First Search for Game Design and Content Generation via a Case Study of Fling!,
    Nathan Sturtevant,
    AI in the Game Design Process (AIIDE workshop)
    [abstract] [pdf] [.bib]

2012

• Benchmarks for Grid-Based Pathfinding,
  Nathan R. Sturtevant,
  Transactions on Computational Intelligence and AI in Games
  [abstract] [pdf] [.bib]

• Partial-expansion A* with Selective Node Generation,
  A. Felner, M. Goldenberg, G. Sharon, R. Stern, Nathan Sturtevant, R. C. Holte and Jonathan Schaeffer,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Conflict-Based Search For Optimal Multi-Agent Path Finding,
  G. Sharon, R. Stern, A. Felner and N. Sturtevant,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• ArvandHerd: Parallel Planning with a Portfolio,
  R. Valenzano, H. Nakhost, M. Muller, J. Schaeffer and N. Sturtevant,
  European Conference on Artificial Intelligence (ECAI 2012)
  [abstract] [pdf] [.bib]

• Meta-Agent Conflict-Based Search For Optimal Multi-Agent Path Finding,
  Guni Sharon, Roni Stern, Ariel Felner and Nathan R. Sturtevant,
  Symposium on Combinatorial Search (SoCS)
  Note: Won SoCS 2012 best paper award
  [abstract] [pdf] [.bib]

  Short Papers, Workshops, Others

  • Moving Path Planning Forward,
    Nathan R. Sturtevant,
    Motion in Games (MIG)
    [abstract] [pdf] [.bib]

  • Heuristic Search Comes of Age,
    Nathan R. Sturtevant, Ariel Felner, Maxim Likhachev and Wheeler Ruml,
    AAAI Conference on Artificial Intelligence
    [abstract] [pdf] [.bib]

2011

• Inconsistent heuristics in theory and practice,
  A. Felner, U. Zahavi, R. Holte, J. Schaeffer, N. Sturtevant and Z. Zhang,
  Artificial Intelligence (AIJ)
  [abstract] [pdf] [.bib]

• A GGP feature learning algorithm,
  M. Kirci, N. Sturtevant and J. Schaeffer,
  KI-Kunstliche Intelligenz
  [abstract] [pdf] [.bib]

• The Compressed Differential Heuristic,
  Meir Goldenberg, Nathan R. Sturtevant, Ariel Felner and Jonathan Schaeffer,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Euclidean Heuristic Optimization,
  C. Rayner, M. Bowling and N. Sturtevant,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Learning where you are going and from whence you came: h-and g-cost learning in real-time heuristic search,
  N.R. Sturtevant and V. Bulitko,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• A Polynomial-Time Algorithm for Non-Optimal Multi-Agent Pathfinding,
  M.M. Khorshid, R.C. Holte and N.R. Sturtevant,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• A Sparse Grid Representation for Dynamic Three-Dimensional Worlds,
  N.R. Sturtevant,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [.bib]

• Real-Time Heuristic Search for Pathfinding in Video Games,
  Vadim Bulitko, Yngvi Bjornsson, Nathan R. Sturtevant and Ramon Lawrence,
  Applied Research in Artificial Intelligence for Computer Games
  [.bib]

  Short Papers, Workshops, Others

  • A Demonstration of ScriptEase II,
    M. Church, E. Graves, J. Duncan, A. Lari, R. Miller, N. Desai, R. Zhao, M. Carbonaro, J. Schaeffer, N. Sturtevant and others,
    Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
    [abstract] [pdf] [.bib]

  • ArvandHerd: Parallel Planning with a Portfolio,
    R. Valenzano, H. Nakhost, M. Muller, J. Schaeffer and N. Sturtevant,
    Proc. 7th International Planning Competition (IPC 2011)
    [.bib]

  • Distance Learning in Agent-Centered Heuristic Search,
    N.R. Sturtevant,
    Annual Symposium on Combinatorial Search (SoCS)
    [abstract] [pdf] [.bib]

2010

• Single-Frontier Bidirectional Search,
  Ariel Felner, Carsten Moldenhauer, Nathan R. Sturtevant and Jonathan Schaeffer,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• Understanding the Success of Perfect Information Monte Carlo Sampling in Game Tree Search,
  J. Long, N.R. Sturtevant, M. Buro and T. Furtak,
  AAAI Conference on Artificial Intelligence
  [abstract] [pdf] [.bib]

• On learning in agent-centered search,
  N.R. Sturtevant, V. Bulitko and Y. Bjornsson,
  Autonomous Agents and Multiagent Systems (AAMAS)
  [abstract] [pdf] [.bib]

• Simultaneously Searching with Multiple Settings: An Alternative to Parameter Tuning for Suboptimal Single-Agent Search Algorithms,
  Richard A. Valenzano, Nathan R. Sturtevant, Jonathan Schaeffer, Karen Buro and Akihiro Kishimoto,
  International Conference on Automated Planning and Scheduling (ICAPS)
  [abstract] [pdf] [.bib]

• Portal-based true-distance heuristics for path finding,
  M. Goldenberg, A. Felner, N. Sturtevant and J. Schaeffer,
  Symposium on Combinatorial Search (SoCS)
  [abstract] [pdf] [.bib]

• A comparison of high-level approaches for speeding up pathfinding,
  N.R. Sturtevant and R. Geisberger,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [.bib]

• Implementing games on pinball machines,
  D. Wong, D. Earl, F. Zyda, R. Zink, S. Koenig, A. Pan, S. Shlosberg, J. Singh and N. Sturtevant,
  Proceedings of the Fifth International Conference on the Foundations of Digital Games
  [abstract] [pdf] [.bib]

2009

• TBA*: Time-Bounded A*,
  Y. Bjornsson, V. Bulitko and N. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Improving state evaluation, inference, and search in trick-based card games,
  M. Buro, J.R. Long, T. Furtak and N. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Evaluating strategies for running from the cops,
  C. Moldenhauer and N.R. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Learning when to stop thinking and do something!,
  B. Poczos, Y. Abbasi-Yadkori, C. Szepesvari, R. Greiner and N. Sturtevant,
  International Conference on Machine Learning (ICML)
  [abstract] [pdf] [.bib]

• Memory-based heuristics for explicit state spaces,
  N. R. Sturtevant, A. Felner, M. Barer, J. Schaeffer and N. Burch,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• A* search with inconsistent heuristics,
  Z. Zhang, N.R. Sturtevant, R. Holte, J. Schaeffer and A. Felner,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Abstraction-based heuristics with true distance computations,
  A. Felner, N. Sturtevant and J. Schaeffer,
  Symposium on Abstraction, Reformulation and Approximation
  [abstract] [pdf] [.bib]

• Optimizing motion-constrained pathfinding,
  N.R. Sturtevant,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [.bib]

  Short Papers, Workshops, Others

  • Optimal solutions for moving target search,
    C. Moldenhauer and N.R. Sturtevant,
    Autonomous Agents and Multiagent Systems (AAMAS)
    [abstract] [pdf] [.bib]

  • Feature Learning Using State Differences,
    Mesut Kirci, Jonathan Schaeffer and Nathan Sturtevant,
    IJCAI Workshop on General Game Playing
    [abstract] [pdf] [.bib]

  • Comparing UCT versus CFR in Simultaneous Games,
    Mohammad Shafiei, Nathan Sturtevant and Jonathan Schaeffer,
    IJCAI Workshop on General Game Playing
    [abstract] [pdf] [.bib]

2008

• An Analysis of UCT in Multi-Player Games,
  Nathan R. Sturtevant,
  ICGA Journal
  [abstract] [pdf] [.bib]

• Multidisciplinary students and instructors: a second-year games course,
  N.R. Sturtevant, H.J. Hoover, J. Schaeffer, S. Gouglas, M.H. Bowling, F. Southey, M. Bouchard and G. Zabaneh,
  ACM Special Interest Group on Computer Science Education (SIGCSE)
  [abstract] [pdf] [.bib]

• Direction maps for cooperative pathfinding,
  M.R. Jansen and N.R. Sturtevant,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [.bib]

• An analysis of UCT in multi-player games,
  N. Sturtevant,
  Computers and Games
  [abstract] [pdf] [.bib]

• Memory-Efficient Pathfinding Abstractions,
  Nathan Sturtevant,
  AI Programming Wisdom 4
  [.bib]

  Short Papers, Workshops, Others

  • A New Approach to Cooperative Pathfinding,
    R. Jansen and N. Sturtevant,
    Autonomous Agents and Multiagent Systems (AAMAS)
    [abstract] [pdf] [.bib]

  • Optimized Algorithms for Multi-Agent Routing,
    A. Kishimoto and N. Sturtevant,
    Autonomous Agents and Multiagent Systems (AAMAS)
    [abstract] [pdf] [.bib]

  • Coarse-to-Fine Search Techniques,
    K. Anderson, N. Sturtevant, R. Holte and J. Schaeffer,
    [abstract] [pdf] [.bib]

2007

• Graph abstraction in real-time heuristic search,
  V. Bulitko, N. Sturtevant, J. Lu and T. Yau,
  Journal of Artificial Intelligence Research (JAIR)
  [abstract] [pdf] [.bib]

• Inconsistent heuristics,
  U. Zahavi, A. Felner, J. Schaeffer and N. Sturtevant,
  Proceedings of the National Conference on Artificial Intelligence (AAAI)
  [abstract] [pdf] [.bib]

• An analysis of map-based abstraction and refinement,
  N. Sturtevant and R. Jansen,
  Symposium on Abstraction, Reformulation and Approximation (SARA)
  [abstract] [pdf] [.bib]

• Memory-efficient abstractions for pathfinding,
  N. Sturtevant,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [.bib]

2006

• Prob-maxn: Opponent modeling in n-player games,
  N. Sturtevant, M. Zinkevich and M. Bowling,
  Proceedings of the National Conference on Artificial Intelligence (AAAI)
  [abstract] [pdf] [.bib]

• Robust game play against unknown opponents,
  N. Sturtevant and M. Bowling,
  Autonomous Agents and Multiagent Systems (AAMAS)
  [abstract] [pdf] [.bib]

• Partial information endgame databases,
  Y. Bjornsson, J. Schaeffer and N. Sturtevant,
  Advances in Computer Games
  [abstract] [pdf] [.bib]

• Feature construction for reinforcement learning in hearts,
  N. Sturtevant and A. White,
  Computers and Games
  [abstract] [pdf] [.bib]

• Improving collaborative pathfinding using map abstraction,
  N. Sturtevant and M. Buro,
  Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
  [abstract] [pdf] [.bib]

  Short Papers, Workshops, Others

  • State abstraction for real-time moving target pursuit: A pilot study,
    Vadim Bulitko and Nathan Sturtevant,
    AAAI Workshop on Learning For Search
    [abstract] [pdf] [.bib]

2005

• Speeding up learning in real-time search via automatic state abstraction,
  V. Bulitko, N. Sturtevant and M. Kazakevich,
  Proceedings of the National Conference on Artificial Intelligence (AAAI)
  [abstract] [pdf] [.bib]

• Leaf-value tables for pruning non-zero-sum games,
  N. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

• Partial pathfinding using map abstraction and refinement,
  N. Sturtevant and M. Buro,
  Proceedings of the National Conference on Artificial Intelligence (AAAI)
  [abstract] [pdf] [.bib]

  Short Papers, Workshops, Others

  • Automatic state abstraction for pathfinding in real-time video games,
    N. Sturtevant, V. Bulitko and M. Buro,
    Symposium on Abstraction, Reformulation and Approximation
    [.bib]

2004

• Current Challenges in Multi-player Game Search,
  Nathan R. Sturtevant,
  Computers and Games
  [abstract] [pdf] [.bib]

2003

• Multi-player games: Algorithms and approaches,
  N.R. Sturtevant,
  [abstract] [pdf] [.bib]

• Last-Branch and Speculative Pruning Algorithms for Maxn,
  N. Sturtevant,
  International Joint Conference on Artificial Intelligence (IJCAI)
  [abstract] [pdf] [.bib]

2002

• A Comparison of Algorithms for Multi-player Games,
  Nathan R. Sturtevant,
  Computers and Games
  [abstract] [pdf] [.bib]

2000

• On pruning techniques for multi-player games,
  N.R. Sturtevant and R.E. Korf,
  Proceedings Of The National Conference On Artificial Intelligence (AAAI)
  [abstract] [pdf] [.bib]

1999

Short Papers, Workshops, Others

• The Information Discovery Graph: towards a scalable multimedia resource directory,
  N.R. Sturtevant, N. Tang and L. Zhang,
  IEEE Workshop on Internet Applications
  [pdf] [.bib]