July 2016 Newsletter

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Research updates A new paper: “A Formal Solution to the Grain of Truth Problem.” The paper was presented at UAI-16, and describes the first general reduction of game-theoretic reasoning to expected utility maximization. Participants in MIRI’s recently-concluded Colloquium Series on Robust and Beneficial AI (CSRBAI) have put together AI safety environments for the OpenAI Reinforcement Learning Gym.1 Help is welcome creating more… Read more »

New paper: “A formal solution to the grain of truth problem”

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Future of Humanity Institute Research Fellow Jan Leike and MIRI Research Fellows Jessica Taylor and Benya Fallenstein have just presented new results at UAI 2016 that resolve a longstanding open problem in game theory: “A formal solution to the grain of truth problem.” Game theorists have techniques for specifying agents that eventually do well on… Read more »

June 2016 Newsletter

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Research updates New paper: “Safely Interruptible Agents.” The paper will be presented at UAI-16, and is a collaboration between Laurent Orseau of Google DeepMind and Stuart Armstrong of the Future of Humanity Institute (FHI) and MIRI; see FHI’s press release. The paper has received (often hyperbolic) coverage from a number of press outlets, including Business… Read more »

New paper: “Safely interruptible agents”

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Google DeepMind Research Scientist Laurent Orseau and MIRI Research Associate Stuart Armstrong have written a new paper on error-tolerant agent designs, “Safely interruptible agents.” The paper is forthcoming at the 32nd Conference on Uncertainty in Artificial Intelligence. Abstract: Reinforcement learning agents interacting with a complex environment like the real world are unlikely to behave optimally… Read more »

May 2016 Newsletter

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Research updates Two new papers split logical uncertainty into two distinct subproblems: “Uniform Coherence” and “Asymptotic Convergence in Online Learning with Unbounded Delays.” New at IAFF: An Approach to the Agent Simulates Predictor Problem; Games for Factoring Out Variables; Time Hierarchy Theorems for Distributional Estimation Problems We will be presenting “The Value Learning Problem” at… Read more »

April 2016 Newsletter

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Research updates A new paper: “Parametric Bounded Löb’s Theorem and Robust Cooperation of Bounded Agents“ New at IAFF: What Does it Mean for Correct Operation to Rely on Transfer Learning?; Virtual Models of Virtual AIs in Virtual Worlds General updates We’re currently accepting applicants to two programs we’re running in June: our 2016 Summer Fellows… Read more »

New paper on bounded Löb and robust cooperation of bounded agents

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MIRI Research Fellow Andrew Critch has written a new paper on cooperation between software agents in the Prisoner’s Dilemma, available on arXiv: “Parametric bounded Löb’s theorem and robust cooperation of bounded agents.” The abstract reads: Löb’s theorem and Gödel’s theorem make predictions about the behavior of systems capable of self-reference with unbounded computational resources with… Read more »

Announcing a new colloquium series and fellows program

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The Machine Intelligence Research Institute is accepting applicants to two summer programs: a three-week AI robustness and reliability colloquium series (co-run with the Oxford Future of Humanity Institute), and a two-week fellows program focused on helping new researchers contribute to MIRI’s technical agenda (co-run with the Center for Applied Rationality). The Colloquium Series on Robust… Read more »