— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
We introduce an online adaptive algorithm for learning gesture models. By learning gesture models in an online fashion, the gesture recognition process is made more robust, and th...
This paper presents a novel approach for adaptive online multi-stroke sketch recognition based on Hidden Markov Model (HMM). The method views the drawing sketch as the result of a ...
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
The problem of reinforcement learning in large factored Markov decision processes is explored. The Q-value of a state-action pair is approximated by the free energy of a product o...