jessicata

Jessica Taylor. CS undergrad and Master's at Stanford; former research fellow at MIRI.

I work on decision theory, social epistemology, strategy, naturalized agency, mathematical foundations, decentralized networking systems and applications, theory of mind, and functional programming languages.

Comments

Thoughts on Voting Methods

I agree that moving to distributions and scalar utility is a good way of avoiding Pareto suboptimal outcomes.

Thoughts on Voting Methods

FPTP would be if there weren't more points awarded for winning by more votes.

Here is an example of an election.

3 prefer A > B > C

4 prefer B > C > A

5 prefer C > A > B

(note, this is a Condorcet cycle)

Now we construct the following payoff matrix for a zero sum game, where the number given is for the utility of the row player:

\ A B C

A 0 4 -6

B -4 0 2

C 6 -2 0

This is basically rock paper scissors, except that the A strategy wins twice as much when it wins as the C strategy does, and the B strategy wins 3 times as much as the C strategy does.

This game's unique Nash equilibrium picks A 1/6 of the time, B 1/2 of the time, C 1/3 of the time. So this is the probability of the candidates being elected.

Thoughts on Voting Methods

I don't know what you are saying is the case.

Thoughts on Voting Methods

Curious what you think of Consistent Probabilistic Social Choice.

My summary:

There is a unique consistent voting system in cases where the system may return a stochastic distribution of candidates!

(where consistent means: grouping together populations that agree doesn't change the result, and neither does duplicating candidates)

What is the rule? Take a symmetric zero-sum game where each player picks a candidate, and someone wins if their candidate is preferred by the majority to the other, winning more points if they are preferred by a larger majority. This game's Nash equilibrium is the distribution.

The Bayesian Tyrant

The basic point here is that Bayesians lose zero sum games in the long term. Which is to be expected, because Bayesianism is a non adversarial epistemology. (Adversarial Bayesianism is simply game theory)

This sentence is surprising, though: "It is a truth more fundamental than Bayes’ Law that money will flow from the unclever to the clever".

Clearly, what wins zero sum games wins zero sum games, but what wins zero sum games need not correspond to collective epistemology.

As a foundation for epistemology, many things are superior to "might makes right", including Bayes' rule (despite its limitations).

Legislating Bayesianism in an adversarial context is futile; mechanism design is what is needed.

Many-worlds versus discrete knowledge

Thanks! To the extent that discrete branches can be identified this way, that solves the problem. This is pushing the limits of my knowledge of QM at this point so I'll tag this as something to research further at a later point.

Many-worlds versus discrete knowledge

I'm not asking for there to be a function to the entire world state, just a function to observations. Otherwise the theory does not explain observations!

(aside: I think Bohm does say there is a definite answer in the cat case, as there is a definite configuration that is the true one; it's Copenhagen that fails to say it is one way or the other)

Many-worlds versus discrete knowledge

Then you need a theory of how the continuous microstate determines the discrete macrostate. E.g. as a function from reals to booleans. What is that theory in the case of the wave function determining photon measurements?

Many-worlds versus discrete knowledge

I'm saying that our microphysical theories should explain our macrophysical observations. If they don't then we toss out the theory (Occam's razor).

Macrophysical observations are discrete.

Many-worlds versus discrete knowledge

Let me know if anyone succeeds at that. I've thought in this direction and found it very difficult.

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