title: Deep Neural Network combined with qlearning
body: <p>I'm using joint positions from a Kinect camera as my state space but I think it's going to be too large (25 joints x 30 per second) to just feed into SARSA or Qlearning. </p>
  
  <p>Right now I'm using the Kinect Gesture Builder program which uses Supervised Learning to associate user movement to specific gestures. But that requires supervised training which I'd like to move away from. I figure the algorithm might pick up certain associations between joints that I would when I classify the data myself (hands up, step left, step right, for example). </p>
  
  <p>I think feeding that data into a deep neural network and then pass that into a reinforcement learning algorithm might give me a better result. </p>
  
  <p>There was a paper on this recently. <a href="https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf" rel="nofollow">https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf</a></p>
  
  <p>I know Accord.net has both deep neural networks and RL but has anyone combined them together? Any insights? </p>