{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-quality-value-dqv-learning","title":"Deep Quality-Value (DQV) Learning","arxiv_id":"1810.00368","date":"2018-09-30","proceeding":null,"authors":["Matthia Sabatelli","Gilles Louppe","Pierre Geurts","Marco A. Wiering"],"abstract":"We introduce a novel Deep Reinforcement Learning (DRL) algorithm called Deep\nQuality-Value (DQV) Learning. DQV uses temporal-difference learning to train a\nValue neural network and uses this network for training a second Quality-value\nnetwork that learns to estimate state-action values. We first test DQV's update\nrules with Multilayer Perceptrons as function approximators on two classic RL\nproblems, and then extend DQV with the use of Deep Convolutional Neural\nNetworks, `Experience Replay' and `Target Neural Networks' for tackling four\ngames of the Atari Arcade Learning environment. Our results show that DQV\nlearns significantly faster and better than Deep Q-Learning and Double Deep\nQ-Learning, suggesting that our algorithm can potentially be a better\nperforming synchronous temporal difference algorithm than what is currently\npresent in DRL.","url_abs":"http://arxiv.org/abs/1810.00368v2","url_pdf":"http://arxiv.org/pdf/1810.00368v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-quality-value-dqv-learning","repo_url":"https://github.com/paintception/Deep-Quality-Value-DQV-Learning-","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"deep-quality-value-dqv-learning","repo_url":"https://github.com/paintception/Deep-Quality-Value-Family","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"deep-quality-value-dqv-learning","repo_url":"https://github.com/paintception/Deep-Quality-Value-Family-","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"atari-games","task_name":"Atari Games"},{"task_slug":"deep-reinforcement-learning","task_name":"Deep Reinforcement Learning"},{"task_slug":"q-learning","task_name":"Q-Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[{"method_slug":"q-learning","method_name":"Q-Learning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}