Learning for Adaptive Real-time Search

Learning for Dynamic subsumption

Learning from Profession Knowledge: Application on Knitting

Learning from Scarce Experience

Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap

Learning in Real-Time Search: A Unifying Framework

Learning invariant features through local space contraction

Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree search

Learning Multi-modal Similarity

Learning Nonlinear Dynamic Models

Learning Performance of Prediction Markets with Kelly Bettors

Learning Polynomial Networks for Classification of Clinical Electroencephalograms

Learning Probabilistic Hierarchical Task Networks to Capture User Preferences

Learning RoboCup-Keepaway with Kernels

Learning to automatically detect features for mobile robots using second-order Hidden Markov Models

Learning to Bluff

Learning to Coordinate Efficiently: A Model-based Approach

Learning to Order BDD Variables in Verification

Learning to Rank Query Recommendations by Semantic Similarities

Learning unbelievable marginal probabilities