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How not to sort by a complicated frequentist formula
In How Not To Sort By Average Rating, Evan Miller gives two wrong ways to generate an aggregate rating from a collection of positive and negative votes, and one method he thinks is correct. But the "correct" method is complicated, poorly motivated, insufficiently parameterized, and founded on frequentist statistics. A much simpler model based on a prior beta distribution has more solid theoretical foundation and would give more accurate results.
Evan mentions the sad reality that big organizations are using obviously naive methods. In contrast, more dynamic sites such as Reddit have adopted the model he suggested. But I fear that it would cause irreparable damage if the world settles on this solution.
Should anything be done about it? What can be done?
This is also somewhat meta in that LW also aggregates ratings, and I believe changing the model was once discussed (and maybe the beta model was suggested).
What is the best paper explaining the superiority of Bayesianism over frequentism?
Question in title.
This is obviously subjective, but I figure there ought to be some "go-to" paper. Maybe I've even seen it once, but can't find it now and I don't know if there's anything better.
Links to multiple papers with different focus would be welcome. For my current purpose I have a preference for one that aims low and isn't too long.
Tel Aviv Self-Improvement Meetup Group
I have started the Tel Aviv Self-Improvement Meetup Group. It is not about rationality or LessWrong per se, but it is heavily influenced by rationality dojos and LW posts in the applied rationality, personal optimization and anti-akrasia cluster. As the description says, it is
A group of people helping each other apply rationality to our everyday lives, in order to improve our skills, make the best decisions, become productive and achieve our goals.
If you're interested and in the area, you're welcome to join. If you have any comments or suggestions, based perhaps on experience with similar groups, please share.
Where in the world is the SIAI house?
I am under the impression that there used to be a place called the SIAI house in Santa Clara, which housed the SIAI Visiting Fellows Program. However, this post suggests that it has moved\is moving to an unspecified location in Berkeley. My efforts to find additional information were unsuccessful.
So, does such a house still exist? What is its exact current location? Does it welcome random visitors?
I ask this because I plan to be in San Francisco on 9-11 January, 2011 with a lot of free time on Sunday the 9th, which looks like a great opportunity for a visit.
Mixed strategy Nash equilibrium
Inspired by: Swords and Armor: A Game Theory Thought Experiment
Recently, nick012000 has posted Swords and Armor: A Game Theory Thought Experiment. I was disappointed to see many confused replies to this post, even after a complete solution was given by Steve_Rayhawk. I thought someone really ought to post an explanation about mixed strategy Nash equilibria. Then I figured that that someone may as well be me.
I will assume readers are familiar with the concepts of a game (a setting with several players, each having a choice of strategies to take and a payoff which depends on the strategies taken by all players) and of a Nash equilibrium (an "optimal" assignment of strategies such that, if everyone plays their assigned strategy, no player will have a reason to switch to a different strategy). Some games, like the famous prisoner's dilemma, have a Nash equilibrium in so-called "pure strategies" (as opposed to mixed strategies, to be introduced later). Consider, however, the following variant of the matching pennies game:
Player 1 is a general leading an attacking army, and player 2 is the general of the defending army. The attacker can attack from the east or west, and the defender can concentrate his defenses on the east or west. By the time each side learns the strategy of its enemy, it is too late to switch strategies. Attacking where the defenses aren't concentrated gives a great advantage; additionally, due to unspecified tactical circumstances, attacking from the east gives a slight advantage. The sides have no interest in cooperating, so this is a zero-sum game (what one side wins, the other loses).
This elaborate description can be summarized in the following payoff matrix (these payoffs are for the attacker; the defender's payoffs are their negatives):
| 2: East | 2: West | |
| 1: East | -1 | 2 |
| 1: West | 1 | -2 |
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