Parrondo's Paradox
en.wikipedia.org
en.wikipedia.org
Corollary: If you take two mutually dependent events and somehow break the dependence between the two, then the events are no longer dependent and therefore by law of conditional probability and law of independent events, you can influence the probability of the outcome of the combination.
A practical example of the corollary would be password re-entry user interfaces during account registration.
The reason while re-entering the password the second time, we are not shown what we typed earlier is to make the reentry independent of the previous entry. Otherwise, we may look at what was typed earlier and subconsciously type the same thing -- which would be bad while we are doing account registration.
In this case has the game not become Game A + Game B ?
It's just a larger game with a distinct winning strategy because the ruleset is expanded right?
What's the significance?
1) Hitting both nails and screws with a hammer is a losing game.
2) Screwing both nails and screws with a screwdriver is a losing game.
Paradox alert! If you hammer the nails and screw the screws you've transformed two losing games into a winning game!
1) Wearing shorts and sandals all year round is a losing game (in this part of the world); you will freeze to death in the winter.
2) Wearing your warmest clothing all year round is a losing game; you will overheat in the summer.
This is a paradox, because the population of Canada should be zero. But wait! What if you just dress appropriately for the season?
Start with: 1 large fixed size data structure and 1 cache Algorithm A: Checks as it is iterating whether the cache is full. If not, it generates the cache data (SLOW) but can then iterate over the entire data structure quickly. First time it does this is a loss, but 2nd pass through the data structure leads to an overall win. Algorithm B: Prefers an empty cache. If cache is full it will delete it. It can iterate over the entire data structure fairly quickly. Each time is considered a win.
Now you have a program with many different features and everyone knows that it doesn't really matter if you use Algorithm A or B because they are both programmed to work safely together and if you test a feature using one of the algorithms it will be fast either way, so it's left up to personal preference. The fun begins when the full program starts alternating from algorithm A to B.
> It's a physicist¹ proving that we need integration tests.
¹ Juan Parrondo is a physicist by training, not a mathematician.Let's try to make it HN-relevant by asking:
can two things that both AB tested positively in independent one-at-a-time testing possibly backfire if you launch both of them?
This is similar to the 'ratchet' examples in the wikipedia page - you play the game with the best odds, and use one game to 'cool off' until you're in the right state to win the second game again. The games in the wikipedia article are kinda unsatisfying, though - there's too much dependence on player state.
> In summary, Parrondo's paradox is an example of how dependence can wreak havoc with probabilistic computations made under a naive assumption of independence.
In other words, this is a load of time-wasting BS, based on doing a stupid thing at the outset anyone thinking clearly sees right away.
[1] By which I mean these are strategies that are strictly dominated in the game-theory sense.
On your turn, you secretly roll a die and then make a statement about what number you rolled. The next player may then call your bluff. If you lied, you lose, otherwise they lose. Or they may roll again, but must claim to have rolled something higher than whatever you rolled. If you don't lose, you win.
Suppose you have to explain your (mixed, i.e. involving randomness) strategy to other players before playing. This is a simulation of the realistic situation of playing many times and other players learning your strategy.
Let us examine the situation where you are given a 4 from the previous player and you decided to roll. (You would have to prove that this can be a correct move, but what follows is in principle true in any situation where you roll.)
If you roll a 5 or 6, you say so. But if you roll a lower number, you have to claim a 5 or 6 regardless. If you announce a 6, you lose instantly, because the next player has no chance of rolling higher, so they must call your bluff. Thus in a single game the correct move is to announce a 5.
But since the other players know your strategy, you can increase you chances of them believing you have a 5 if you sometimes claim a 6 and thereby forefeit the game. It is an easy calculation to see that this strategy yields more wins than always claiming a 5 in this situation.
I think this is analogue to the poker example: Play a clearly bad move and thus gain an advantage by being unpredictable. In my example it is not so hard to see that the advantage can in principle outweigh the cost of playing bad moves.
For people who don't know the so-called fundamental theorem of poker[1] was proposed by David Sklansky who was definitely more mathematically-minded than most poker players of his generation but was not really a mathematician. It's gained a lot of mindshare even though it's clearly at odds with game theory. Probably this is because it's very simple to state and seems intuitive. It is usually stated as something like "Every time you play a hand differently than you would have if you could see all your opponent's cards you lose and they gain and vice versa, and conversely every time they play a hand differently from how they would if they could see all your cards you gain and they lose and vice versa".
This is one of those things that sounds sort of obviously correct and so is very seductive as an idea, but it completely fails if you just think for a second about the fact that you can't see their cards and they can't see your cards. In that world (actual poker), we know that the optimal strategy is a Nash equilibrium in mixed strategies(we know this is true for all games of hidden information). By definition that means you are sometimes doing something different from "what you would do if you could see their cards", because you have a mixed strategy (ie you don't do exactly the same thing every time but choose options with some randomness). The same is true for the opponent. Therefore we can see that it follows trivially that the "fundamental theorem" can't be correct.
[1] https://en.wikipedia.org/wiki/Fundamental_theorem_of_poker
Granted maybe this article is good and just beyond me, but it is disappointing how much Wikipedia is like that.
To be said, this article is not graspable at first for me either. There is the "even simpler example"[0], but I am not even sure if it is a right example (different games can share a state, the amount of money), or just an analogy.
[0] : https://en.wikipedia.org/wiki/Parrondo's_paradox#The_simple_...
I was really confused how anyone could glaze over with such a concise description, but they saw something different than I did.
Unrelated, but I always want to link permanent wiki articles, but there is no culture for it, and I am afraid it would annoy people because it is uncommon.
> The role of M now comes into sharp focus. It serves solely to induce a dependence between Games A and B, so that a player is more likely to enter states in which Game B has a positive expectation, allowing it to overcome the losses from Game A. With this understanding, the paradox resolves itself: The individual games are losing only under a distribution that differs from that which is actually encountered when playing the compound game. In summary, Parrondo's paradox is an example of how dependence can wreak havoc with probabilistic computations made under a naive assumption of independence.
Trying to rephrase: if you combine systems in a way that the rules of the combination itself serves to "manipulate" the individual conditions of the two systems, then you can get positive outcomes from two things that, individually, would give negative outcomes if not otherwise manipulated. The example with the even simpler "In Game B, you count how much money you have left — if it is an even number you win $3, otherwise you lose $5." (compared to the game where the above quote came from) really sums that up - if you know your starting point you can set up the sequence of those two games to steadily win.
The important parts here are that in game A you lose slower than in game B's losing sub-game, and game B's sub-games switch depending on the resources you win/lose in game A.
The strategy is to play game A until you hit the conditions for game B's winning sub-game to kick in, then play game B until it swaps back over again, then go back to A and repeat the process.
Thus two games where each have negative expected value, can be daisy chained to produce positive expected value.
The interviewer (who knows he has a positive diagnosis), sensing easy money, plays along, and an exam ensues on the spot.
The candidate pronounces that the interviewer is clear. The interviewer produces the diagnosis, and demands to be paid.
The candidate shrugs and produces the money. The interviewer notes the sanguine candidate and asks if this is the usual ending.
The candidate laughs and says that he had a $10k bet with the interviewer's competitor that he'd have his finger up the interviewer's backside in under an hour.
In summary, the paradox in The Famous Article seems to boil down to https://en.wikipedia.org/wiki/Arbitrage
It seems like if you have 2 games A and B, the second you start playing them together you’ve effectively created a new game C, which is a game of A and B combined.
You do:
> but it’s definitely surprising and non intuitive.
That's a common definition of a paradox: "a seemingly absurd or self-contradictory statement or proposition that when investigated or explained may prove to be well founded or true."
Suppose you have a game where your score is A*B. The strategy to only increase A or only increase B are losing ones, but combining them gives a winning strategy.
The resolution is "stop hitting yourself".
The idea that a combination of two losing things can be a winning thing specifically doesn't seem intuitive. Lots of game-theoretic analyses involve decomposing a complex game into different situatons and trying to solve each situation seperately. Especially for hidden information games with multiple rounds (eg Poker or card games generally). The assumption underlying this approach is by combining winning strategies together you can approximate an overall optimal solution breaks down in the face of this given that you might need to include all combinations of losing things also since those losing strategies may combine to form a winning strategy overall.
We die at the end and all we've accumulated doesn't worth a thing. Game over.
But paradoxically, by being alive, playfull and involved in playing the loosing game of life we win... moment after moment.