5 ms·

You don't consider AIXI part of the actual AI research community? Also, AIXI is non-computable, but AIXItl is.

by sanxiyn 11y ago

sampo 11y ago
> You don't consider AIXI part of the actual AI research community? I just briefly tried to read up on AIXI. The concept is ...not without merit, but I think it totally sweeps the central problem (We have no idea how to program an AI) under the rug in two ways: (1) The problem of programming ...programming anything at all, is swept under the rug by assuming a formalism in which every possible algorithm/program can be enumerated, and then just using brute force to go through, essentially search though all the character strings that represent implementations of any kind of algorithms, however bad they might be. (2) The problem of trying to decide what we actually should want to do in complex situations is swept under the rug by just assuming that we have access to a reward function that tells the desirability of each outcome at each step. So if this kind of helpful assumptions are allowed, the problem of, say, constructing a good chess program can be easily solved by the following meta-algorithm: 1. List all chess programs 2. Choose the best one There, problem solved!
- chriswarbo 11y ago
  You're right, of course; AIXI doesn't attempt to tackle the practical problem of building an AI. However, it does give us a concrete, non-hand-wavey algorithm which can reasonably be considered "AI, if we ignore resource constraints". Consider that it took ~50 years to go from the inception of AI to a formal model like AIXI; or ~40 years from the definition of NP-completeness (ie. the realisation that scalability and resource usage are the real challenges for AI). In that sense, AIXI provides two things: a hypothetical "gold standard" for AI builders to compare their research to; and a formal model which can be studied right now by those who aren't directly building AIs (like MIRI). Consider an analogy to space flight. The engineering contains all kinds of resource constraints (eg. launch mass, strength-to-weight ratios, etc.), but it's still useful to ignore them temporarily and ask: what if we had as much fuel as we could ever want? What if we could keep the crew frozen during the journey? and so on. In other words, if we manage to overcome our current difficulties, what could we actually do with this tech?
  - eli_gottlieb 11y ago
    >However, it does give us a concrete, non-hand-wavey algorithm which can reasonably be considered "AI, if we ignore resource constraints". No, not really. "If we ignore resource constraints" is ignoring most of the problem. Using Kolmogorov complexity in the Solomonoff Measure also constitutes ignoring the problem of generalization by assuming an optimal compressor into existence, which again is an issue of the cognitive resources of training data and processing power. Bayesian updating means it will achieve optimal expected reward, but also that AIXI can be "fooled" by the hierarchical nature of real environments' variance[1]. And the whole thing pays no attention to knowledge representation whatsoever. It's basically a grand victory for the fields of AI and Machine Learning that still tells us basically nothing about how an actually existing, embodied mind has to function, except that statistical learning is most likely the core mechanism in some fashion (after all, neural networks show that the real thing isn't even necessarily Bayesian in any sense). [1] Benjamin B. Machta, Ricky Chachra, Mark K. Transtrum, and James P. Sethna. Parameter space compression underlies emergent theories and predictive models. Science, 342(6158):604–607, 2013.
    - chriswarbo 11y ago
      > It's basically a grand victory for the fields of AI and Machine Learning that still tells us basically nothing about how an actually existing, embodied mind has to function Special relativity tells us basically nothing about how an actually existing, physical spaceship has to function; but it does constrain our speculation about space travel (ie. no FTL, the fact that accelerating massive objects requires more and more energy, etc.). It also provides some handy little suggestions that we may not have anticipated; eg. that mass can be converted into energy, which is certainly useful when trying to come up with practical designs.
      - sampo 11y ago
        > constrain But AIXI, I don't see how it constrains anything. It introduces a classification: AIXI type algorithms, and other algorithms. But we don't really know if this is a useful segmentation of the search space, or perhaps as useless as considering the merits of red spaceships vs. spaceships painted with other color.
anonmeow 11y ago
AIXI was neither invented by MIRI nor have they proved any nontrivial theorems about it. AIXI is Marcus Hutter's work: http://www.hutter1.net/ai/aixigentle.htm http://www.hutter1.net/ai/aixigentle.htm
- shoo 11y ago
  Indeed! From a superficial inspection, Hutter's back catalogue features 89 * @inproceedings, 3 * @book, 12 * @techreport, 51 * @article, and 1 * @compression prize Over an elapsed period of '87 (from before he had completed his masters degree) to the present, on a published_artefacts/year basis, Hutter is more productive than MIRI.
  - eli_gottlieb 11y ago
    Of course, how many of those publications are Yet Another AIXI Paper?
  - rndn 11y ago
    What’s up with this publish or perish nonsense? If you are concerned that MIRI works on problems that are disconnected from reality, then read their papers and provide a thorough analysis.

You don't consider AIXI part of the actual AI research community? Also, AIXI is non-computable, but AIXItl is.

by sanxiyn 11y ago

You don't consider AIXI part of the actual AI research community? Also, AIXI is non-computable, but AIXItl is.

sampo 11y ago

> You don't consider AIXI part of the actual AI research community? I just briefly tried to read up on AIXI. The concept is ...not without merit, but I think it totally sweeps the central problem (We have no idea how to program an AI) under the rug in two ways: (1) The problem of programming ...programming anything at all, is swept under the rug by assuming a formalism in which every possible algorithm/program can be enumerated, and then just using brute force to go through, essentially search though all the character strings that represent implementations of any kind of algorithms, however bad they might be. (2) The problem of trying to decide what we actually should want to do in complex situations is swept under the rug by just assuming that we have access to a reward function that tells the desirability of each outcome at each step. So if this kind of helpful assumptions are allowed, the problem of, say, constructing a good chess program can be easily solved by the following meta-algorithm: 1. List all chess programs 2. Choose the best one There, problem solved!

chriswarbo 11y ago
You're right, of course; AIXI doesn't attempt to tackle the practical problem of building an AI. However, it does give us a concrete, non-hand-wavey algorithm which can reasonably be considered "AI, if we ignore resource constraints". Consider that it took ~50 years to go from the inception of AI to a formal model like AIXI; or ~40 years from the definition of NP-completeness (ie. the realisation that scalability and resource usage are the real challenges for AI). In that sense, AIXI provides two things: a hypothetical "gold standard" for AI builders to compare their research to; and a formal model which can be studied right now by those who aren't directly building AIs (like MIRI). Consider an analogy to space flight. The engineering contains all kinds of resource constraints (eg. launch mass, strength-to-weight ratios, etc.), but it's still useful to ignore them temporarily and ask: what if we had as much fuel as we could ever want? What if we could keep the crew frozen during the journey? and so on. In other words, if we manage to overcome our current difficulties, what could we actually do with this tech?
- eli_gottlieb 11y ago
  >However, it does give us a concrete, non-hand-wavey algorithm which can reasonably be considered "AI, if we ignore resource constraints". No, not really. "If we ignore resource constraints" is ignoring most of the problem. Using Kolmogorov complexity in the Solomonoff Measure also constitutes ignoring the problem of generalization by assuming an optimal compressor into existence, which again is an issue of the cognitive resources of training data and processing power. Bayesian updating means it will achieve optimal expected reward, but also that AIXI can be "fooled" by the hierarchical nature of real environments' variance[1]. And the whole thing pays no attention to knowledge representation whatsoever. It's basically a grand victory for the fields of AI and Machine Learning that still tells us basically nothing about how an actually existing, embodied mind has to function, except that statistical learning is most likely the core mechanism in some fashion (after all, neural networks show that the real thing isn't even necessarily Bayesian in any sense). [1] Benjamin B. Machta, Ricky Chachra, Mark K. Transtrum, and James P. Sethna. Parameter space compression underlies emergent theories and predictive models. Science, 342(6158):604–607, 2013.
  - chriswarbo 11y ago
    > It's basically a grand victory for the fields of AI and Machine Learning that still tells us basically nothing about how an actually existing, embodied mind has to function Special relativity tells us basically nothing about how an actually existing, physical spaceship has to function; but it does constrain our speculation about space travel (ie. no FTL, the fact that accelerating massive objects requires more and more energy, etc.). It also provides some handy little suggestions that we may not have anticipated; eg. that mass can be converted into energy, which is certainly useful when trying to come up with practical designs.
    - sampo 11y ago
      > constrain But AIXI, I don't see how it constrains anything. It introduces a classification: AIXI type algorithms, and other algorithms. But we don't really know if this is a useful segmentation of the search space, or perhaps as useless as considering the merits of red spaceships vs. spaceships painted with other color.

anonmeow 11y ago

AIXI was neither invented by MIRI nor have they proved any nontrivial theorems about it. AIXI is Marcus Hutter's work: http://www.hutter1.net/ai/aixigentle.htm http://www.hutter1.net/ai/aixigentle.htm

shoo 11y ago
Indeed! From a superficial inspection, Hutter's back catalogue features 89 * @inproceedings, 3 * @book, 12 * @techreport, 51 * @article, and 1 * @compression prize Over an elapsed period of '87 (from before he had completed his masters degree) to the present, on a published_artefacts/year basis, Hutter is more productive than MIRI.
- eli_gottlieb 11y ago
  Of course, how many of those publications are Yet Another AIXI Paper?
- rndn 11y ago
  What’s up with this publish or perish nonsense? If you are concerned that MIRI works on problems that are disconnected from reality, then read their papers and provide a thorough analysis.