👁 1
💬 0
📄 Extracted Text (919 words)
From: "Jeffrey E." <[email protected]>
To: Joscha Bach
Subject: Re: Decision making
Date: Wed, 26 Aug 2015 20:48:57 +0000
not sure of course. but trying many things , finding a solution and repeating it until it no longer works. . to
find the series solution to 7 19 37 88. is virtually impossible , but merely the diffefrence of cubes„ how do you
get to that answer.? or how do you find food? ::))
On Wed, Aug 26, 2015 at 4:44 PM, Joscha Bach < wrote:
So you are suggesting that probabilities are not the best way to frame decision making? (We can overcome
things like independence, at the cost of sufficiently complex models, and in a world without repetition = some
kind of regularity, all bets are off, but of course probabilistic models might still be impractical in practice.)
What would be a better framework?
Am 26.08.2015 um 16:39 schrieb jeffrey E. <[email protected]>:
probablities vs similiarities. I suggest you take care with the concept of probabilites which really requires
repetition, symmetry, and independence.
On Wed, Aug 26, 2015 at 4:26 PM, Joscha Bach < > wrote:
1. Does luck mean gambling, or getting the probabilities right by intuition?
2. What else tells you anything about the future? (The past also tells us how much is does not tell us about
the future)
Am 26.08.2015 urn 16:23 schrieb jeffrey E. <[email protected]>:
luck plays a role. 2 , looking back ( bayesian ) might not tell you anthing about the future.
On Wed, Aug 26, 2015 at 3:44 PM, Joscha Bach < > wrote:
Re motivation: Have you seen the recent movie "Ex Machina"? I liked it; one of the few Al movies that
have not been dumbed down. The main character is a beautiful female looking Al, clearly intelligent,
and able to manipulate humans to an arbitrary degree. What makes her inhuman is that she is probably
motivated by a single principle, like option maximization. That would make her an inscrutable
psychopath. Option maximization would entail energy, physical integrity, perhaps reproduction,
certainly learning, but you will have an agent that you won't like to share a prisoner's dilemma with.
How do you approach decision making? I have recently learned that people that subscribe for Cryonics
(freezing one's head or body in the hope to be revived when future technologies make it possible)
assign a lower probability to that it works than the general population. But whereas "normal" people
tend to make binary models about the world: something is "probably not going to work, so let us not
bother", many of the Cryonics folks will argue that paying $500 a month for a 1% chance of
immortality seems like a bargain.
This seems to generalize: in principle, we should perform a Bayesian approximation for all our major
decisions, attach probability distributions to everything in the space of possible beliefs, and be able to
outperform the vast majority of folks that relies on narratives (i.e. binary yes/no decisions about the
facts in the world). Gigerenzer, Kahnemann and many others have shown that human brains are terrible
EFTA00847721
of getting this intuitively right, to the point where an absence of fine-grained domain knowledge often
leads to better management decisions etc.
The divide between probabilistic models vs. narrative models is reflected to some degree in the conflict
between probabilistic and logic based AI. In practice, we will probably need to combine both, but I
wonder if there is an intrinsic limit to probabilistic descriptions in a highly complex world, where we
cannot observe baseline probabilities anyway.
How do you decide? Do you Solomonoff-induce and Bayes the hell out of the stock market, do you
reason, do you soak up data and let your intuitions guide you, or is most of the important stuff
depending on communication and negotiation? Is there are general approach, or how much should
theories of decision making be dependent on the domain?
Cheers,
Joscha
please note
The information contained in this communication is
confidential, may be attorney-client privileged, may
constitute inside information, and is intended only for
the use of the addressee. It is the property of
JEE
Unauthorized use, disclosure or copying of this
communication or any part thereof is strictly prohibited
and may be unlawful. If you have received this
communication in error, please notify us immediately by
return e-mail or by e-mail to [email protected], and
destroy this communication and all copies thereof,
including all attachments. copyright -all rights reserved
please note
The information contained in this communication is
confidential, may be attorney-client privileged, may
constitute inside information, and is intended only for
the use of the addressee. It is the property of
JEE
Unauthorized use, disclosure or copying of this
communication or any part thereof is strictly prohibited
and may be unlawful. If you have received this
communication in error, please notify us immediately by
return e-mail or by e-mail to jeevacation®gmail.com, and
destroy this communication and all copies thereof,
including all attachments. copyright -all rights reserved
EFTA00847722
please note
The information contained in this communication is
confidential, may be attorney-client privileged, may
constitute inside information, and is intended only for
the use of the addressee. It is the property of
JEE
Unauthorized use, disclosure or copying of this
communication or any part thereof is strictly prohibited
and may be unlawful. If you have received this
communication in error, please notify us immediately by
return e-mail or by e-mail to [email protected], and
destroy this communication and all copies thereof,
including all attachments. copyright -all rights reserved
EFTA00847723
ℹ️ Document Details
SHA-256
0ba4bc98f285943d308d4add5d4d70240d5c09750a4163bcedec0e17836f4df9
Bates Number
EFTA00847721
Dataset
DataSet-9
Type
document
Pages
3
💬 Comments 0