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» Learning with Continuous Experts Using Drifting Games
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ICDM
2009
IEEE
111views Data Mining» more  ICDM 2009»
14 years 3 months ago
A Game Theoretical Model for Adversarial Learning
Abstract—It is now widely accepted that in many situations where classifiers are deployed, adversaries deliberately manipulate data in order to reduce the classifier’s accura...
Wei Liu, Sanjay Chawla
MICCAI
2008
Springer
14 years 2 months ago
Soft Tissue Tracking for Minimally Invasive Surgery: Learning Local Deformation Online
Accurate estimation and tracking of dynamic tissue deformation is important to motion compensation, intra-operative surgical guidance and navigation in minimally invasive surgery. ...
Peter Mountney and Guang-Zhong Yang
AAAI
2012
11 years 11 months ago
Learning from Demonstration for Goal-Driven Autonomy
Goal-driven autonomy (GDA) is a conceptual model for creating an autonomous agent that monitors a set of expectations during plan execution, detects when discrepancies occur, buil...
Ben George Weber, Michael Mateas, Arnav Jhala
GECCO
2008
Springer
178views Optimization» more  GECCO 2008»
13 years 9 months ago
Agent Smith: a real-time game-playing agent for interactive dynamic games
The goal of this project is to develop an agent capable of learning and behaving autonomously and making decisions quickly in a dynamic environment. The agent’s environment is a...
Ryan K. Small
ICANN
2010
Springer
13 years 8 months ago
Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients
Abstract. Developing superior artificial board-game players is a widelystudied area of Artificial Intelligence. Among the most challenging games is the Asian game of Go, which, des...
Mandy Grüttner, Frank Sehnke, Tom Schaul, J&u...