But once you assign randomness so that it can have some range of values then it becomes more problematic. And, if you can just assign the randomness to some characteristics of the data, then there is even more room for non-intuitive uses. For instance, we might say that randomness is the normalized inverse of the probability of an event occurrence. This complicates the abstract boundary-discovery process since it might turn out that our experiences with similar events have been limited and part of what we are calling randomness is merely that which we have not yet understood - relative to the statistical definition of the event in this case. But I appreciate your explanation of Algorithmic Randomness relative to AIT and Kolmogorov Complexity. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T682f141cc89b5183-M1ee7d424a3b29614e150d1ae Delivery options: https://agi.topicbox.com/groups/agi/subscription
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