[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-pirate-ai-q-learning-treasure-agent-en":3,"article-related-pirate-ai-q-learning-treasure-agent-en":20,"series-industry-0c87c77c-199e-4990-9308-69e6582e251e":63},{"id":4,"slug":5,"title":6,"content":7,"summary":8,"source":9,"source_url":10,"author":11,"image_url":12,"cover_image":12,"category":13,"language":14,"translated_content":11,"related_article_id":15,"keywords":11,"key_takeaways":11,"views":16,"created_at":17,"published_at":18,"topic_cluster_id":19},"0c87c77c-199e-4990-9308-69e6582e251e","pirate-ai-q-learning-treasure-agent-en","Pirate-AI trains a treasure-seeking Q-learning agent","\u003Cp data-speakable=\"summary\">Pirate-AI is a Jupyter Notebook project that trains a pirate \u003Ca href=\"\u002Ftag\u002Fagent\">agent\u003C\u002Fa> with deep Q-learning to reach treasure.\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fquestmcclure\u002FPirate-AI\" target=\"_blank\" rel=\"noopener\">Pirate-AI\u003C\u002Fa> is a tiny but instructive \u003Ca href=\"\u002Ftag\u002Freinforcement-learning\">reinforcement learning\u003C\u002Fa> project: one \u003Ca href=\"\u002Ftag\u002Fgithub\">GitHub\u003C\u002Fa> star, zero forks, and a notebook-based implementation focused on path finding. The goal is simple to state and hard to make work well in code, which is why this repo is interesting.\u003C\u002Fp>\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>Metric\u003C\u002Fth>\u003Cth>Value\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd>Repository\u003C\u002Ftd>\u003Ctd>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fquestmcclure\u002FPirate-AI\" target=\"_blank\" rel=\"noopener\">questmcclure\u002FPirate-AI\u003C\u002Fa>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Stars\u003C\u002Ftd>\u003Ctd>1\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Forks\u003C\u002Ftd>\u003Ctd>0\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Language\u003C\u002Ftd>\u003Ctd>Jupyter Notebook\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Learning method\u003C\u002Ftd>\u003Ctd>Deep Q-learning\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Ch2>What this project is trying to do\u003C\u002Fh2>\u003Cp>The repository frames the problem as a pirate trying to reach treasure by learning which actions produce the best outcome over time. Instead of hard-coding a route, the agent learns from reward signals, state transitions, and repeated episodes of play.\u003C\u002Fp>\u003Cp>That makes this more than a toy navigation demo. It is a compact example of how reinforcement learning turns a sequence of choices into a policy, with the model gradually preferring actions that lead to better returns.\u003C\u002Fp>\u003Cp>The README says the project was built in \u003Ca href=\"https:\u002F\u002Fwww.python.org\u002F\" target=\"_blank\" rel=\"noopener\">Python\u003C\u002Fa> with \u003Ca href=\"https:\u002F\u002Fkeras.io\u002F\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778418633516-5txc.png\" alt=\"Pirate-AI trains a treasure-seeking Q-learning agent\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778418637774-ot8b.png\" alt=\"Pirate-AI trains a treasure-seeking Q-learning agent\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n","Pirate-AI is a Jupyter Notebook project that trains a pirate agent with deep Q-learning to find treasure more reliably.","github.com","https:\u002F\u002Fgithub.com\u002Fquestmcclure\u002FPirate-AI",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778418633516-5txc.png","industry","en","000c31c0-8cff-487d-a7ab-30ed1090178f",8,"2026-05-10T13:10:19.154828+00:00","2026-05-10T13:10:19.145+00:00","af98df97-3941-46a0-a0fe-c349d1547327",{"tags":21,"relatedLang":22,"relatedPosts":26},[],{"id":15,"slug":23,"title":24,"language":25},"pirate-ai-q-learning-treasure-agent-zh","Pirate-AI：用 Q-learning 找寶藏","zh",[27,33,39,45,51,57],{"id":28,"slug":29,"title":30,"cover_image":31,"image_url":31,"created_at":32,"category":13},"c189d18f-0ae1-4b87-9f42-ec0d97f32c1f","ethereum-institutional-nonprofit-banks-government-en","Ethereum Launches Institution-Focused Nonprofit","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1783319580529-r9nh.png","2026-07-06T06:32:32.513127+00:00",{"id":34,"slug":35,"title":36,"cover_image":37,"image_url":37,"created_at":38,"category":13},"fe9e97e5-6a81-4eff-a759-d29bcc3ec759","ethereum-institutional-standard-chartered-backing-en","Ethereum Institutional wins backing from Standard Chartered","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1783317802111-z3ho.png","2026-07-06T06:02:51.47182+00:00",{"id":40,"slug":41,"title":42,"cover_image":43,"image_url":43,"created_at":44,"category":13},"5444f5dd-df7e-462d-97da-aa4dc019d905","ai-weekly-2026-w28-en","AI Weekly: 2026-06-29 ~ 2026-07-06","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1783311624710-lsrj.png","2026-07-06T04:00:29.632651+00:00",{"id":46,"slug":47,"title":48,"cover_image":49,"image_url":49,"created_at":50,"category":13},"60bda9b1-b32c-42cd-ba70-3ed9a634d8a5","daily-huggingface-ai-papers-research-updates-en","Daily HuggingFace AI Papers keeps research moving","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1783301567170-ezfg.png","2026-07-06T01:32:21.757509+00:00",{"id":52,"slug":53,"title":54,"cover_image":55,"image_url":55,"created_at":56,"category":13},"53fee7f6-0100-44f6-b8c8-58bdb5d66fea","ai-companion-rules-app-rollbacks-explained-en","AI Companion Rules and App Rollbacks Explained","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1783299903391-qh1b.png","2026-07-06T01:02:37.588693+00:00",{"id":58,"slug":59,"title":60,"cover_image":61,"image_url":61,"created_at":62,"category":13},"f4b84c44-2607-43b8-bae5-0533122d7121","meta-ai-infrastructure-bet-compute-sales-en","Meta’s $182.9B AI bet may need compute sales","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1783297980883-32ib.png","2026-07-06T00:32:32.225736+00:00",[64,69,74,79,84,89,94,99,104,109],{"id":65,"slug":66,"title":67,"created_at":68},"d35a1bd9-e709-412e-a2df-392df1dc572a","ai-impact-2026-developments-market-en","AI's Impact in 2026: Key Developments and Market Shifts","2026-03-25T16:20:33.205823+00:00",{"id":70,"slug":71,"title":72,"created_at":73},"5ed27921-5fd6-492e-8c59-78393bf37710","trumps-ai-legislative-framework-en","Trump's AI Legislative Framework: What's Inside?","2026-03-25T16:22:20.005325+00:00",{"id":75,"slug":76,"title":77,"created_at":78},"e454a642-f03c-4794-b185-5f651aebbaca","nvidia-gtc-2026-key-highlights-innovations-en","NVIDIA GTC 2026: Key Highlights and Innovations","2026-03-25T16:22:47.882615+00:00",{"id":80,"slug":81,"title":82,"created_at":83},"0ebb5b16-774a-4922-945d-5f2ce1df5a6d","claude-usage-diversifies-learning-curves-en","Claude Usage Diversifies, Learning Curves Emerge","2026-03-25T16:25:50.770376+00:00",{"id":85,"slug":86,"title":87,"created_at":88},"69934e86-2fc5-4280-8223-7b917a48ace8","openclaw-ai-commoditization-concerns-en","OpenClaw's Rise Raises Concerns of AI Model Commoditization","2026-03-25T16:26:30.582047+00:00",{"id":90,"slug":91,"title":92,"created_at":93},"b4b2575b-2ac8-46b2-b90e-ab1d7c060797","google-gemini-ai-rollout-2026-en","Google's Gemini AI Rollout Extended to 2026","2026-03-25T16:28:14.808842+00:00",{"id":95,"slug":96,"title":97,"created_at":98},"6e18bc65-42ae-4ad0-b564-67d7f66b979e","meta-llama4-fabricated-results-scandal-en","Meta's Llama 4 Scandal: Fabricated AI Test Results Unveiled","2026-03-25T16:29:15.482836+00:00",{"id":100,"slug":101,"title":102,"created_at":103},"bf888e9d-08be-4f47-996c-7b24b5ab3500","accenture-mistral-ai-deployment-en","Accenture and Mistral AI Team Up for AI Deployment","2026-03-25T16:31:01.894655+00:00",{"id":105,"slug":106,"title":107,"created_at":108},"5382b536-fad2-49c6-ac85-9eb2bae49f35","mistral-ai-high-stakes-2026-en","Mistral AI: Facing High Stakes in 2026","2026-03-25T16:31:39.941974+00:00",{"id":110,"slug":111,"title":112,"created_at":113},"9da3d2d6-b669-4971-ba1d-17fdb3548ed5","cursors-meteoric-rise-pressures-en","Cursor's Meteoric Rise Faces Industry Pressures","2026-03-25T16:32:21.899217+00:00"]