Reinforcement Learning in Newcomblike Problems

N/A

# link_g0l4g6azxs.pdf ## Metadata - PDFFormatVersion=1.4 - IsLinearized=false - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - Title=Reinforcement Learning in Newcomblike Problems - Producer=macOS Version 10.15 (Build 19A603) Quartz PDFContext - Author=Caspar Oesterheld - Creator=Preview - CreationDate=D:20220124163056Z00'00' - ModDate=D:20220124163056Z00'00' ## Contents ### Page 1 Reinforcement Learning in Newcomblike Environments James BellThe Alan Turing Institute London, UKjbell@posteo.comLinda LinseforsIndependent Researcherlinda.

saved by

• Lydia Nottingham
• Yudhister Joel Kumar
• Bhagyesh Kumar

related reading

• Embedded Agency (full-text version) — LessWronglesswrong.com
• Deep Q-Networks Explained — LessWronglesswrong.com
• Approval-directed agency and the decision theory of Newcomb-like problemslink.springer.com
• A (Long) Peek into Reinforcement Learning | Lil'Loglilianweng.github.io
• Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Reviewarxiv.org
• What is AIXI?jan.leike.name
• Deep Reinforcement Learning: Pong from Pixelskarpathy.github.io
• Part 1: Key Concepts in RL - Spinning Up documentationspinningup.openai.com
• SuttonBartoIPRLBook2ndEd.pdfweb.stanford.edu
• rltheorybook_ABJKS.pdfrltheorybook.github.io
• An Updated Introduction to Reinforcement Learning | Sri's Blogsrianumakonda.com
• RL_Notes__final_.pdfjubayer-ibn-hamid.github.io