Imputation means making up missing input data. Solomonoff induction implies that the most likely values are those that minimize the Kolmogorov complexity of the restored input, and it is not computable in general.
The theoretical motivation for Solomonoff induction is that all probability distributions over an infinite set must favor short descriptions over longer ones. Every description with p > 0 is more likely than an infinite set of longer descriptions. On Fri, Oct 25, 2019, 12:40 AM James Bowery <[email protected]> wrote: > I don't see any theoretic grounding in the prior responses. Isn't "AGI" a > technical term? Imputation of missing data is: > > https://en.wikipedia.org/wiki/Imputation_(statistics) > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > <https://agi.topicbox.com/groups/agi/T36c83eb0aa31fc55-Mc11aa73f4c0a51d88e5af373> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T36c83eb0aa31fc55-M7c4b873a9080fac42de6987b Delivery options: https://agi.topicbox.com/groups/agi/subscription
