[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-35971":3,"doc-seo-35971":29},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},35971,1374391975076,"Riley","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Reinforcement Learning Algorithms A Brief Survey Ashish Kumar Shakya","A brief survey document focused on reinforcement learning algorithms authored by Ashish Kumar Shakya. It highlights the core idea of using agents to learn decision policies through trial-and-error interaction with an environment, aiming to improve cumulative reward. The material provides an overview-style organization that connects key algorithmic approaches, their motivations, and how they are typically applied to sequential decision-making problems.","","cbCailFYfTP3GJ3A","https://ap.wps.com/l/cbCailFYfTP3GJ3A","pdf",2380530,1,32,"English","en",105,"# Overview of Reinforcement Learning\n## Learning Through Interaction and Reward","[{\"question\":\"What is the central goal of reinforcement learning algorithms discussed in the survey?\",\"answer\":\"Reinforcement learning aims to learn decision policies that maximize cumulative reward over time through interaction with an environment.\"},{\"question\":\"How do reinforcement learning methods improve performance according to the survey’s framing?\",\"answer\":\"They improve by using feedback from rewards obtained during exploration and subsequent policy refinement.\"},{\"question\":\"What does a “brief survey” emphasize in this document?\",\"answer\":\"It emphasizes a high-level comparison and organization of major reinforcement learning algorithm approaches rather than a single method in depth.\"}]",1782767101,81,null]