Universal Algorithmic Intelligence
Community hub for researchers interested in Solomonoff Induction, AIXI, etc.
Author: Cole Wyeth
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Marta Kryven will present on approximate Bayesian inference for problem-solving domains at the UAI research meeting tomorrow, Monday February 23rd at 3 pm EST. We will use the regular zoom link. Abstract: Bayesian Inference and Optimal Experiment Design provide a general case optimal theoretical framework for how to build world models and interpret evidence. However,…
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Elija Perrier will discuss his work on quantum mechanical versions of the AIXI agent: https://arxiv.org/abs/2505.21170 The (extra) talk will be tomorrow, Monday Feb 16th at 3 pm EST over the usual zoom link. Bio Elija is a doctoral candidate at the Centre for Quantum Software and Information at the University of Technology Sydney. Elija’s doctoral…
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Dr. Marc Finzi will discuss his work on computationally bounded information theory (“epiplexity”) at this week’s regular research meeting, Monday February 9th at 3 pm ET (at the regular zoom link). Details below. Bio:Marc Finzi is a Research Scientist at OpenAI. He received his Ph.D. in Computer Science from New York University for work on…
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Marcus Hutter will answer any lingering questions on “An Introduction to Universal Artificial Intelligence” at the final meeting of the reading group on Monday, Jan 26th at 12 pm EST = 5 pm GMT. The zoom link is (as usual): https://uwaterloo.zoom.us/j/7921763961?pwd=TDatET6CBu47o4TxyNn9ccL2Ia8HN4.1 Note that the Australasian reading group is several chapters behind and still running.
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The reading group returns on Monday the 12th from a holiday break with a visit from David Quarel, who will answer questions on Chapter 15. With a focus on AI safety, this chapter is mostly less technical, so feel free to jump in here even if you missed some (or all) previous chapters. David has…
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This is a linkpost for https://arxiv.org/abs/2512.17086 This updated version of my (Cole Wyeth’s) AGI 2025 paper with Marcus Hutter, “Value under ignorance in universal artificial intelligence,” studies general utility functions for AIXI. Surprisingly, the (hyper)computability properties have connections to imprecise probability theory! AIXI uses a defective Bayesian mixture called a semimeasure, which is often viewed…
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As the first IUAI reading group draws to a close (in a few weeks), we are happy to share that a second round has already started (on Australian/Asian time) thanks to Sigfrido D. Ciletti! Description: Algorithmic Information Theory (Australasia) reading group. Meeting every week, Tuesday at 12pm AEDT (GMT+11:00) [open invitation]. This is also fairly…
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Alexander Meulemans and Rajai Nasser will discuss their work with Google’s Paradigms of Intelligence Team on eMbedded Universal Predictive Intelligence (MUPI): https://www.arxiv.org/abs/2511.22226 Abstract: The standard theory of model-free reinforcement learning assumes that the environment dynamics are stationary and that agents are decoupled from their environment, such that policies are treated as being separate from the world they…
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Michele Vannucci is a master’s student at Vrije Universiteit and a regular at the AIXI reading group. This week he will present his work on an interesting AIXI variation that minimizes surprise (in contrast to Orseau’s Knowledge-Seeking Agents) at the regular research meeting (3 pm ET tomorrow, Monday November 30th). Title: Universal Surprise-Minimizing Agents Abstract:We…
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Alexis-Walid is a PhD student at Senckenberg who will describe his recent work applying ideas from AIT to evolutionary genetics: Using Hector Zenil’s tools to estimate the Kolmogorov complexity of small strings and matrices, we will see evidence of algorithmicity in genetic network evolution and protein sequences, showing that not only is evolution “aware” of…
Universal Algorithmic Intelligence 