Using dynamic programming to choose a pose on each iteration makes a lot sense, which would give more desirable result than with the method used in “Motion graph” to pick a target motion. Since I am lacking of knowledge on reinforcement learning and autonomous agents, further elaboration on that would be of help. -- Steven Chang
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Using reinforcement learning to allow animated characters to come up with motions is a very neat idea. The authors mentioned that they added in some small actions and allowed for randomness in the model by allowing these actions to be chosen even when they aren’t optimal. Would it not be better if the authors used a HMM instead of a fully observable Markov Model? This would allow for the output states to have a probability distribution that could be randomly sampled and also keep the model more close to reality. -Disha Al Baqui