{"action":"created","issue":{"url":"https://api.github.com/repos/philtabor/Youtube-Code-Repository/issues/9","repository_url":"https://api.github.com/repos/philtabor/Youtube-Code-Repository","labels_url":"https://api.github.com/repos/philtabor/Youtube-Code-Repository/issues/9/labels{/name}","comments_url":"https://api.github.com/repos/philtabor/Youtube-Code-Repository/issues/9/comments","events_url":"https://api.github.com/repos/philtabor/Youtube-Code-Repository/issues/9/events","html_url":"https://github.com/philtabor/Youtube-Code-Repository/issues/9","id":537824633,"node_id":"MDU6SXNzdWU1Mzc4MjQ2MzM=","number":9,"title":"dqn_keras.py choose_action function should have q_next and not q_eval","user":{"login":"Gonm1","id":29556446,"node_id":"MDQ6VXNlcjI5NTU2NDQ2","avatar_url":"https://avatars3.githubusercontent.com/u/29556446?v=4","gravatar_id":"","url":"https://api.github.com/users/Gonm1","html_url":"https://github.com/Gonm1","followers_url":"https://api.github.com/users/Gonm1/followers","following_url":"https://api.github.com/users/Gonm1/following{/other_user}","gists_url":"https://api.github.com/users/Gonm1/gists{/gist_id}","starred_url":"https://api.github.com/users/Gonm1/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Gonm1/subscriptions","organizations_url":"https://api.github.com/users/Gonm1/orgs","repos_url":"https://api.github.com/users/Gonm1/repos","events_url":"https://api.github.com/users/Gonm1/events{/privacy}","received_events_url":"https://api.github.com/users/Gonm1/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2019-12-13T23:36:43Z","updated_at":"2019-12-18T07:07:49Z","closed_at":"2019-12-18T07:07:49Z","author_association":"NONE","body":"I think that, since it is DQN, you have a target network for the predictions at every step and you .fit the q_eval model for the learning, also at every step. This is supposed to help with stability.\r\n\r\nhttps://github.com/philtabor/Youtube-Code-Repository/blob/d70e8cfb640b648d115bd32941549182309d8366/ReinforcementLearning/DeepQLearning/dqn_keras.py#L82"},"comment":{"url":"https://api.github.com/repos/philtabor/Youtube-Code-Repository/issues/comments/566897443","html_url":"https://github.com/philtabor/Youtube-Code-Repository/issues/9#issuecomment-566897443","issue_url":"https://api.github.com/repos/philtabor/Youtube-Code-Repository/issues/9","id":566897443,"node_id":"MDEyOklzc3VlQ29tbWVudDU2Njg5NzQ0Mw==","user":{"login":"philtabor","id":11725813,"node_id":"MDQ6VXNlcjExNzI1ODEz","avatar_url":"https://avatars2.githubusercontent.com/u/11725813?v=4","gravatar_id":"","url":"https://api.github.com/users/philtabor","html_url":"https://github.com/philtabor","followers_url":"https://api.github.com/users/philtabor/followers","following_url":"https://api.github.com/users/philtabor/following{/other_user}","gists_url":"https://api.github.com/users/philtabor/gists{/gist_id}","starred_url":"https://api.github.com/users/philtabor/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/philtabor/subscriptions","organizations_url":"https://api.github.com/users/philtabor/orgs","repos_url":"https://api.github.com/users/philtabor/repos","events_url":"https://api.github.com/users/philtabor/events{/privacy}","received_events_url":"https://api.github.com/users/philtabor/received_events","type":"User","site_admin":false},"created_at":"2019-12-18T07:07:49Z","updated_at":"2019-12-18T07:07:49Z","author_association":"OWNER","body":"The improvement in stability comes from using the target network to evaluate the value of the new states, in the learning function. \r\n\r\nI recommend reading the nature paper to clarify this issue."}}
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