{"guid":"b1740c2f-0c44-5f1b-89ed-456a9eecf0b8","title":"A Competitive Time-Trial AI for Need for Speed: Most Wanted Using Deep Reinforcement Learning","subtitle":null,"slug":"38c3-a-competitive-time-trial-ai-for-need-for-speed-most-wanted-using-deep-reinforcement-learning","link":"https://events.ccc.de/congress/2024/hub/event/a-competitive-time-trial-ai-for-need-for-speed-most-wanted-using-deep-reinforcement-learning/","description":"All challenges and achievements in creating a competitive time-trial AI in NFS:MW.\n\n15 years ago, at the height of my eSports career, I uploaded an (unofficial) ESL record at Need for Speed: Most Wanted (2005) (NFS:MW) to Youtube. In the meantime Deep Reinforcement Learning became popular and ever since I have dreamt of creating a competitive AI for my favorite racing game of all time: NFS:MW. Now finally the time was right: The hardware is fast enough, good software is available, and Sony's AI research has proven the task is actually doable. Hence I thought: \"How hard can it possibly be?\".\n\nThis talk will present in detail all challenges and achievements in creating a competitive time-trial AI in NFS:MW from scratch - including but not limited to - hacking of the game to create a custom API, building a custom (real-time) OpenAI gym environment, steering the game using a virtual controller, and finally successfully training an AI using the Soft-Actor-Critic algorithm. All code including the API is written in Python and is open source.\n\nLicensed to the public under http://creativecommons.org/licenses/by/4.0","original_language":"eng","persons":["Sebastian Schwarz"],"tags":["38c3","42","2024","Hardware \u0026 Making","Saal ZIGZAG"],"view_count":2005,"promoted":false,"date":"2024-12-28T00:15:00.000+01:00","release_date":"2024-12-30T00:00:00.000+01:00","updated_at":"2026-04-16T00:45:04.804+02:00","length":2640,"duration":2640,"thumb_url":"https://static.media.ccc.de/media/congress/2024/42-b1740c2f-0c44-5f1b-89ed-456a9eecf0b8.jpg","poster_url":"https://static.media.ccc.de/media/congress/2024/42-b1740c2f-0c44-5f1b-89ed-456a9eecf0b8_preview.jpg","timeline_url":"https://static.media.ccc.de/media/congress/2024/42-b1740c2f-0c44-5f1b-89ed-456a9eecf0b8.timeline.jpg","thumbnails_url":"https://static.media.ccc.de/media/congress/2024/42-b1740c2f-0c44-5f1b-89ed-456a9eecf0b8.thumbnails.vtt","frontend_link":"https://media.ccc.de/v/38c3-a-competitive-time-trial-ai-for-need-for-speed-most-wanted-using-deep-reinforcement-learning","url":"https://api.media.ccc.de/public/events/b1740c2f-0c44-5f1b-89ed-456a9eecf0b8","conference_title":"38C3: Illegal 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