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How are gaining confidence and optimizing a function not descriptions of the same process expressed in different mediums?

dr_zoidberg 11y ago
Confidence, in the sense that what used in the article (not as in the grade of confidence in a probabilistic sample), has an emotional component. Optimizing a function is adjusting the free parameters to maximize a desired output.
- kingkawn 11y ago
  How is emotion not a feedback system for optimization other than the European prejudice against taking it seriously?
  - adwn 11y ago
    Why should it be a "feedback system"? Maybe it is an unnecessary side effect of our complicated brains? For all we know, consciousness is a prerequisite for emotions, and I seriously doubt that a simple optimization algorithm exhibits consciousness.
    - sgt101 11y ago
      There's no need to doubt - you can see the algorithm written down, there are no symbols spent on consciousness. There are no surges in the network in response to anything apart from the inputs. The sheep, it does not dream - although sometimes I observe them writing on HN.
  - sgt101 11y ago
    I think that you can discover this by experiencing lots of different emotions. People in distress (a strong emotion) often act in a way that we know as self destructive. People in love (another emotion) do dumb things. We see these insights in lots of cultural artefacts from all cultures that I am aware of - books, plays, songs, poems, stories, pictures and statues. If I was to get irritated with your comments would that be optimal?
- thatcat 11y ago
  Emotion is a variable for social groups and it's optimization could be built into an algorithm. Although algorithms don't have confidence as used colloquially, their optimizations could have "confidence intervals" to indicate the scope of conditions in which they have successfully optimized as determined through feedback. If then, the range over which their optimization functions apply are increasing in scope over time, they could be said to be gaining confidence.
  - dr_zoidberg 11y ago
    See in the paper[0] Figure 3 near the end shows the neural networks used for the different scenarios. None of them have a "confidence" input or parameter. As for confidence intervals, that's why I made the distinction originally, the word is not being used in the "formal" sense, but in the emotional sense. [0] http://arxiv.org/pdf/1502.05477v3.pdf http://arxiv.org/pdf/1502.05477v3.pdf
adwn 11y ago
How are they descriptions of the same process? If you understand "optimizing a function" as "getting better at a certain task": A human can get better at a certain task without gaining confidence, and he/she can gain confidence without getting better at a certain task. The two things might be correlated, but they're not the same. The most important difference is that "gaining confidence" is a feeling, and that simulated optimization algorithm does not have feelings.
sgt101 11y ago
I suppose that you can examine the intent, the different mechanisms of achieving the outcome and the outcome itself as surface differences. Orthogonally there are sets of beliefs about the nature of the experience by the entities undertaking the activity. I personally believe that I have a rich and diverse set of motivations and experiences within the process, and that this qualitatively separates confidence gaining and optimisation in a machine which does not have these enrichments into different categories. You may well argue that this is delusion and all I would do is offer to buy you a beer. But taking the features of the two things that can be observed and potentially agreed on I would say that confidence can be gained socially, often it is gained when the skill is sufficient - by which I mean that optimal skill is achieved and yet confidence is not in place - and confidence can be created in a situation where no skill exists. Confidence is subjective and yet absolute, where as optimisation is objective and by degree. I would talk more and buy that beer but there is a pretty girl over there who I like the look of a lot more, bye.

dr_zoidberg 11y ago

Confidence, in the sense that what used in the article (not as in the grade of confidence in a probabilistic sample), has an emotional component. Optimizing a function is adjusting the free parameters to maximize a desired output.

kingkawn 11y ago
How is emotion not a feedback system for optimization other than the European prejudice against taking it seriously?
- adwn 11y ago
  Why should it be a "feedback system"? Maybe it is an unnecessary side effect of our complicated brains? For all we know, consciousness is a prerequisite for emotions, and I seriously doubt that a simple optimization algorithm exhibits consciousness.
  - sgt101 11y ago
    There's no need to doubt - you can see the algorithm written down, there are no symbols spent on consciousness. There are no surges in the network in response to anything apart from the inputs. The sheep, it does not dream - although sometimes I observe them writing on HN.
- sgt101 11y ago
  I think that you can discover this by experiencing lots of different emotions. People in distress (a strong emotion) often act in a way that we know as self destructive. People in love (another emotion) do dumb things. We see these insights in lots of cultural artefacts from all cultures that I am aware of - books, plays, songs, poems, stories, pictures and statues. If I was to get irritated with your comments would that be optimal?
thatcat 11y ago
Emotion is a variable for social groups and it's optimization could be built into an algorithm. Although algorithms don't have confidence as used colloquially, their optimizations could have "confidence intervals" to indicate the scope of conditions in which they have successfully optimized as determined through feedback. If then, the range over which their optimization functions apply are increasing in scope over time, they could be said to be gaining confidence.
- dr_zoidberg 11y ago
  See in the paper[0] Figure 3 near the end shows the neural networks used for the different scenarios. None of them have a "confidence" input or parameter. As for confidence intervals, that's why I made the distinction originally, the word is not being used in the "formal" sense, but in the emotional sense. [0] http://arxiv.org/pdf/1502.05477v3.pdf http://arxiv.org/pdf/1502.05477v3.pdf

adwn 11y ago

How are they descriptions of the same process? If you understand "optimizing a function" as "getting better at a certain task": A human can get better at a certain task without gaining confidence, and he/she can gain confidence without getting better at a certain task. The two things might be correlated, but they're not the same. The most important difference is that "gaining confidence" is a feeling, and that simulated optimization algorithm does not have feelings.

sgt101 11y ago

I suppose that you can examine the intent, the different mechanisms of achieving the outcome and the outcome itself as surface differences. Orthogonally there are sets of beliefs about the nature of the experience by the entities undertaking the activity. I personally believe that I have a rich and diverse set of motivations and experiences within the process, and that this qualitatively separates confidence gaining and optimisation in a machine which does not have these enrichments into different categories. You may well argue that this is delusion and all I would do is offer to buy you a beer. But taking the features of the two things that can be observed and potentially agreed on I would say that confidence can be gained socially, often it is gained when the skill is sufficient - by which I mean that optimal skill is achieved and yet confidence is not in place - and confidence can be created in a situation where no skill exists. Confidence is subjective and yet absolute, where as optimisation is objective and by degree. I would talk more and buy that beer but there is a pretty girl over there who I like the look of a lot more, bye.