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ATAL
2008
Springer
15 years 8 months ago
Expediting RL by using graphical structures
The goal of Reinforcement learning (RL) is to maximize reward (minimize cost) in a Markov decision process (MDP) without knowing the underlying model a priori. RL algorithms tend ...
Peng Dai, Alexander L. Strehl, Judy Goldsmith
AAAI
2010
15 years 7 months ago
Adaptive Transfer Learning
Transfer learning aims at reusing the knowledge in some source tasks to improve the learning of a target task. Many transfer learning methods assume that the source tasks and the ...
Bin Cao, Sinno Jialin Pan, Yu Zhang, Dit-Yan Yeung...
AAAI
2010
15 years 7 months ago
To Max or Not to Max: Online Learning for Speeding Up Optimal Planning
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. b...
Carmel Domshlak, Erez Karpas, Shaul Markovitch
AAAI
2010
15 years 7 months ago
Efficient Belief Propagation for Utility Maximization and Repeated Inference
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
Aniruddh Nath, Pedro Domingos
AAAI
2004
15 years 7 months ago
Spatial Aggregation for Qualitative Assessment of Scientific Computations
Qualitative assessment of scientific computations is an emerging application area that applies a data-driven approach to characterize, at a high level, phenomena including conditi...
Chris Bailey-Kellogg, Naren Ramakrishnan