In nature paper of DQN by DeepMind, DQN is compared to linear function but they does not said what is this linear function? They compared with some linear functions?
0- What is the meaning of this sentences "Each agent was evaluated every 250,000 training frames for 135,000 validation frames" in DQN nature paper?
2- What about meaning of this sentences: "Note that these evaluation episodes were not truncated at 5min leading to higher scores on Enduro"
1- Does this correct:we just put a network with an input and an output? I do not sense why the performance of it is very how?
TheperformanceoftheDQNagentiscomparedwiththeperformanceofalinearfunctionapproximator on the 5 validation games (that is, where a single linear layer was used instead of the convolutional network, in combination with replay and separate target network). Agents were trained for 10 million frames using standard hyper parameters,and three different learning rates. Each agent was evaluated every 250,000 training frames for 135,000 validation frames and the highest average episode score is reported. Note that these evaluation episodes were not truncated at 5 min leading to higher scores on Enduro than the one s reported in Extended Data Table2. Note so that the number of training frames was shorter (10 million frames) as compared to the main results presented in Extended Data Table 2 (50 million frames).