We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Abstract— The mapping and localization problems have received considerable attention in robotics recently. The exploration problem that drives mapping has started to generate sim...
Recent work on online auctions for digital goods has explored the role of optimal stopping theory — particularly secretary problems — in the design of approximately optimal on...
Mohammad Taghi Hajiaghayi, Robert D. Kleinberg, Tu...
Time-triggered architectures (TTAs) are strong candidate platforms for safety-critical real-time applications. A typical time-triggered architecture is constituted by one or more ...
Kathy Dang Nguyen, P. S. Thiagarajan, Weng-Fai Won...