AIXI

AIXI ['ai̯k͡siː] is a theoretical mathematical formalism for artificial general intelligence.It combines Solomonoff induction with sequential… (More)
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1974-2017
051019742017

Papers overview

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2016
2016
  • 2016
We implemented the algorithm for learning and planning in partially observable Markov decision processes described in A Monte… (More)
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2015
2015
Solomonoff induction and AIXI model their environment as an arbitrary Turing machine, but are themselves uncomputable. This fails… (More)
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2015
2015
How could we solve the machine learning and the artificial intelligence problem if we had infinite computation? Solomonoff… (More)
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2012
2012
We consider extending the AIXI agent by using multiple (or even a compact class of) priors. This has the benefit of weakening the… (More)
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2012
2012
One of the key challenges in AIXI approximation is model class approximation i.e. how to meaningfully approximate Solomonoff… (More)
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Highly Cited
2011
Highly Cited
2011
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. Our approach is… (More)
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2011
2011
We identify principles characterizing Solomonoff Induction by demands on an agent’s external behaviour. Key concepts are… (More)
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2010
2010
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is… (More)
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2008
2008
Universal induction solves in principle the problem of choosing a prior to achieve optimal inductive inference. The AIXI theory… (More)
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2003
2003
Decision theory formally solves the problem of rational agents in uncertain worlds if the true environmental prior probability… (More)
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