While the explosion of on-line information has brought new opportunities for nding and using electronic data, it has also brought to the forefront the problem of isolating useful ...
Robin D. Burke, Kristian J. Hammond, Benjamin C. Y...
Almost any information you might want is becoming available on-line. The problem is how to find what you need. One strategy to improve access to existing information sources, is i...
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to real-world problems. Unfortun...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
It is challenging to support the timeliness of realtime data service requests in data-intensive real-time applications such as online auction or stock trading, while maintaining t...