On Sat, Sep 26, 2020, 10:32 PM TimTyler <[email protected]> wrote: > On 2020-09-22 12:45:PM, Matt Mahoney wrote: > > The no free lunch theorem is based on the false premise that it is > > possible to have a uniform probability distribution over an infinite > > set. The converse proves Occam's Razor. > > I don't think that's right. I looked here: > > https://en.wikipedia.org/wiki/No_free_lunch_theorem#Original_NFL_theorems > > It plainly says it is talking about a "finite set". >
Exactly. And our universe is finite. This, all sets of real objects must be finite too. So why doesn't the no free lunch theorem work in practice. Why are some search algorithms faster than others in practice? Likewise, all of computer science is based on an impossible model of computers with infinite memory. In reality, all computers are finite state machines. This invalidates the halting theorem and all its implications, like Rice's theorem which says that perfectly reliable software testing is not possible, and AIXI, which says optimal prediction and AI are not computable. It invalidates Occam's Razor, essentially all of science. And yet... ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Ta433301e9ac5fb42-Mdae5aefb1011eac94537ce41 Delivery options: https://agi.topicbox.com/groups/agi/subscription
