Collaborated with:David Churchill Marius Stanescu Nicolas A. Barriga Timothy Furtak N.R.Sturtevant Douglas Rebstock Christopher Solinas M. Renee Jansen Graham Kurtis Stephen Erickson Shuyi Zhang Michael Chung J.Schaeffer Franisek Sailer M.Lanctot Abdallah Saffidine Nicolas Arturo Barriga Marius Adrian Stanescu Richard Kelly Andy Hess Sergio Poo Hernandez Graham Erickson Russel Greiner
Talks about:search (10) game (10) craft (8) star (8) strategi (5) combat (4) time (4) real (4) competit (3) polici (3)
Person: Michael Buro
DBLP: Buro:Michael
Contributed to:
2005
200620072007201020112012201320132014201420152016201720172019Wrote 25 papers:
- CIG-2005-ChungBS #game studies #monte carlo
- Monte Carlo Planning in RTS Games (MC, MB, JS).
- AIIDE-2006-SturtevantB #abstraction #collaboration #using
- Improving Collaborative Pathfinding Using Map Abstraction (NRS, MB), pp. 80–85.
- AIIDE-2007-JansenB
- HPA* Enhancements (MRJ, MB), pp. 84–87.
- CIG-2007-SailerBL #simulation
- Adversarial Planning Through Strategy Simulation (FS, MB, ML), pp. 80–87.
- AIIDE-2010-FurtakB #complexity #game studies #graph #on the
- On the Complexity of Two-Player Attrition Games Played on Graphs (TF, MB).
- AIIDE-2011-ChurchillB #optimisation #order
- Build Order Optimization in StarCraft (DC, MB).
- AIIDE-2012-BuroC #contest
- AIIDE 2012 StarCraft Competition (MB, DC).
- AIIDE-2012-ChurchillSB #game studies #heuristic #performance
- Fast Heuristic Search for RTS Game Combat Scenarios (DC, AS, MB).
- AIIDE-2013-BuroC #contest
- AIIDE 2013 StarCraft Competition (MB, DC).
- AIIDE-2013-StanescuHEGB #predict
- Predicting Army Combat Outcomes in StarCraft (MS, SPH, GE, RG, MB).
- CIG-2013-ChurchillB #scalability #simulation
- Portfolio greedy search and simulation for large-scale combat in starcraft (DC, MB), pp. 1–8.
- CIG-2013-FurtakB #game studies #monte carlo #recursion
- Recursive Monte Carlo search for imperfect information games (TF, MB), pp. 1–8.
- AIIDE-2014-BuroC #contest
- AIIDE 2014 StarCraft Competition (MB, DC).
- AIIDE-2014-EricksonB #evaluation
- Global State Evaluation in StarCraft (GKSE, MB).
- AIIDE-2014-StanescuBB #game studies #realtime
- Hierarchical Adversarial Search Applied to Real-Time Strategy Games (MS, NAB, MB).
- CIG-2014-BarrigaSB #parallel
- Parallel UCT search on GPUs (NAB, MS, MB), pp. 1–7.
- AIIDE-2015-BarrigaSB #behaviour #game studies #realtime
- Puppet Search: Enhancing Scripted Behavior by Look-Ahead Search with Applications to Real-Time Strategy Games (NAB, MS, MB), pp. 9–15.
- AIIDE-2015-ChurchillB #architecture #game studies #robust #scalability
- Hierarchical Portfolio Search: Prismata's Robust AI Architecture for Games with Large Search Spaces (DC, MB), pp. 16–22.
- AIIDE-2015-StanescuBB #predict #using
- Using Lanchester Attrition Laws for Combat Prediction in StarCraft (MAS, NAB, MB), pp. 86–92.
- CIG-2016-StanescuBHB #game studies #network #realtime #using
- Evaluating real-time strategy game states using convolutional neural networks (MS, NAB, AH, MB), pp. 1–7.
- AIIDE-2017-BarrigaSB #game studies #learning #realtime
- Combining Strategic Learning with Tactical Search in Real-Time Strategy Games (NAB, MS, MB), pp. 9–15.
- CIG-2017-ZhangB #learning #policy
- Improving hearthstone AI by learning high-level rollout policies and bucketing chance node events (SZ, MB), pp. 309–316.
- CoG-2019-ChurchillBK #optimisation #robust
- Robust Continuous Build-Order Optimization in StarCraft (DC, MB, RK), pp. 1–8.
- CoG-2019-RebstockSB #learning #policy
- Learning Policies from Human Data for Skat (DR, CS, MB), pp. 1–8.
- CoG-2019-RebstockSBS #game studies #policy
- Policy Based Inference in Trick-Taking Card Games (DR, CS, MB, NRS), pp. 1–8.