Dynamic Formations in Real-Time Strategy Games Marcel van der Heijden, Sander Bakkes, and Pieter Spronck A. Formations Abstract— Current approaches to organising units in strategic video games are typically implemented

Source URL: www.csse.uwa.edu.au

• Video game development
• Software
• Gaming
• Artificial intelligence
• Video game bot
• Phalanx
• Machine learning
• Real-time strategy
• Formation

Using Memory Errors to Attack a Virtual Machine Sudhakar Govindavajhala ∗ Andrew W. Appel Princeton University {sudhakar,appel}@cs.princeton.edu Abstract

Source URL: css.csail.mit.edu

Machine Reading Using Markov Logic Networks for Collective Probabilistic Inference Shalini Ghosh, Natarajan Shankar, Sam Owre Computer Sciences Laboratory, SRI International Abstract. DARPA’s Machine Reading project i

Source URL: www.csl.sri.com

Waveform Shape Recognition for Vertical Profiling with an Ensemble of Support Vector Machines Greg Brown December 11, 2009 Abstract

Source URL: greg.ichneumon.net

• Waveform
• Support vector machine
• MOS Technology SID
• Electronics
• Wave
• Computing
• Electromagnetism

Learning Graph Matching Tib´erio S. Caetano, Li Cheng, Quoc V. Le and Alex J. Smola Statistical Machine Learning Program, NICTA and ANU Canberra ACT 0200, Australia Abstract As a fundamental problem in pattern recogniti

Source URL: tiberiocaetano.com

ON THE COMPUTABILITY OF CONDITIONAL PROBABILITY NATHANAEL L. ACKERMAN, CAMERON E. FREER, AND DANIEL M. ROY Abstract. As inductive inference and machine learning methods in computer science see continued success, research

Source URL: danroy.org

Explaining AdaBoost Robert E. Schapire Abstract Boosting is an approach to machine learning based on the idea of creating a highly accurate prediction rule by combining many relatively weak and inaccurate rules. The AdaB

Source URL: rob.schapire.net

Optimal rates for random Fourier feature kernel approximations∗ Zolt´an Szab´o (Gatsby Unit, University College London)† Abstract: Kernel methods represent one of the most powerful tools in machine learning to tac

Source URL: www.gatsby.ucl.ac.uk

Optimal Rates for the Random Fourier Feature Method∗ Zolt´an Szab´o (Gatsby Unit, University College London) Abstract: Kernel methods represent one of the most powerful tools in machine learning to tackle problems ex

Source URL: www.gatsby.ucl.ac.uk

Predicting Player Behavior in Tomb Raider: Underworld Tobias Mahlmann, Anders Drachen, Julian Togelius, Alessandro Canossa and Georgios N. Yannakakis Abstract—This paper presents the results of an explorative study on

Source URL: game.itu.dk

• Software
• Gaming
• Digital media
• Tomb Raider series
• Windows games
• Video game development
• Game design
• Action-adventure games
• Prediction
• Dynamic game difficulty balancing
• Machine learning
• Tomb Raider