The problem is underspecified. I think the post is really operating under the assumption that each generation Omega takes the population, divides it in triples, kills the remaining 0-2 without issue, runs the PD, and takes the result as the population for the next generation.* But if (as the post seems to say) Omega replaces each triple by its children before picking the next triple, exercise 1 is considerably more difficult than the others. In the first version, the agents care only about their children and not the children of other agents or of defectbot. But in the second case, an agent might encounter someone else’s child when it plays the game, so it does care about the proportion of population. Then the situation is not a 1-shot PD and cannot be analyzed so simply. In particular, the answer depends on the utility function. It is not enough to say that the agent prefers more children to fewer; the answer depends on how much.
Consider the modified situation in which I claim that a homogeneous population of TDT/UDT agents defect. In this version, Omega picks replaces a triple with its children before picking the new triples. The payoffs depend on on the number of triples Omega has run: defection is always 1 copy, but cooperation by the N-th triple is worth N copies. If everyone cooperates, the population grows quadratically. There is a chance that an agent will never get picked. A population of sufficiently risk-averse agents will prefer to defect and get 1 child with probability 1 over cooperating and risking having no children. (There are some anthropic issues here, but I don’t think that they matter.)
I had to change a lot of details to get there, but that means that the answer to Exercise 1 must depend on those details. If Omega replaces population every trial, then it cannot be analyzed like a triple in isolation, but must consider the population and utility function explicitly. If Omega runs it generation by generation, then exercise does reduce to an isolated triple. But since the agents only care about their children, they only care about what happens the first generation, and don’t care whether Omega runs any more generations, making the other questions about later generations seem out of place.
* If you change the payoffs from 2⁄3 to 6⁄9, then there are no stragglers to kill. Or you could let the stragglers survive to to play next generation; if the population is large enough, this will not affect strategy.
But in the second case, an agent might encounter someone else’s child when it plays the game, so it does care about the proportion of population.
I don’t understand what you mean by this.
Consider the modified situation in which I claim that a homogeneous population of TDT/UDT agents defect...
Here, I believe you’re saying that you can pick a rate of growth in the payoffs such that, with probability 1, if everyone cooperates, then eventually one particular lineage (chosen randomly) comes to dominate to the extent that nobody else even gets selected to reproduce, and if the starting utility functions are all sufficiently long-term and risk-averse, they might prefer not to undergo that lottery. Is that right?
Your restatement of my example is correct, though the utility functions being long-term is not supposed to distinguish my example from yours. In a generational model where all the children happen at a predetermined time, discounting is not an issue. Your example seems to say that the agents care about the number of children (not descendents) that they have, regardless of when they occur. If they care about their infinite descendents they need discounting to get a finite number. If they care about exponentially discounted children, even with your payoffs and linear utility, they might choose to defect if the discount rate is high enough.
But in the second case, an agent might encounter someone else’s child when it plays the game, so it does care about the proportion of population.
I don’t understand what you mean by this.
My version is exaggerated so that the question is whether an agent gets to play the game at all. With the original constant payoffs, every agent gets put in some triple (with probability 1), so a homogeneous population of TDT agents cooperate. Now go back to your payoffs and consider a mix of TDT and defectors with Omega doing the triples one at a time. The only interesting strategy question for the TDT agent is whether to cooperate against 1 defector or to act cliquey. To decide the expected utility of a strategy, the agent must compute the probability of the different triples it might encounter. These depend on the population when it gets picked, which depend on the strategy it chose. In order to answer exercise 1, it must do exercises 2-4 and more. It is unlikely to encounter the asymptotic population, but it is also unlikely to encounter the original population.
Here’s a rough calculation. Let’s start with 1 defector. Let’s assume that it encounters 2 of the original agents, not their descendents. Let’s further assume its immediate children encounter original agents, not descendents (a quite unreasonable assumption); and that they don’t get picked together, but face 2 TDT agents. Then the difference between cooperating and acting cliquey is 3 encounters with a defector against 9 such encounters. The number of children lost to such an encounter (compared to 3 TDTs) is 5 or 6, depending on cooperating or acting cliquey, which is quite large compared to the 1 that is gained by cooperating rather than acting cliquey. The assumption is ridiculous and the answer with linear utility is probably to cooperate, but it requires calculation and depends on the utility function (and maybe the initial population).
The problem is underspecified. I think the post is really operating under the assumption that each generation Omega takes the population, divides it in triples, kills the remaining 0-2 without issue, runs the PD, and takes the result as the population for the next generation.* But if (as the post seems to say) Omega replaces each triple by its children before picking the next triple, exercise 1 is considerably more difficult than the others. In the first version, the agents care only about their children and not the children of other agents or of defectbot. But in the second case, an agent might encounter someone else’s child when it plays the game, so it does care about the proportion of population. Then the situation is not a 1-shot PD and cannot be analyzed so simply. In particular, the answer depends on the utility function. It is not enough to say that the agent prefers more children to fewer; the answer depends on how much.
Consider the modified situation in which I claim that a homogeneous population of TDT/UDT agents defect. In this version, Omega picks replaces a triple with its children before picking the new triples. The payoffs depend on on the number of triples Omega has run: defection is always 1 copy, but cooperation by the N-th triple is worth N copies. If everyone cooperates, the population grows quadratically. There is a chance that an agent will never get picked. A population of sufficiently risk-averse agents will prefer to defect and get 1 child with probability 1 over cooperating and risking having no children. (There are some anthropic issues here, but I don’t think that they matter.)
I had to change a lot of details to get there, but that means that the answer to Exercise 1 must depend on those details. If Omega replaces population every trial, then it cannot be analyzed like a triple in isolation, but must consider the population and utility function explicitly. If Omega runs it generation by generation, then exercise does reduce to an isolated triple. But since the agents only care about their children, they only care about what happens the first generation, and don’t care whether Omega runs any more generations, making the other questions about later generations seem out of place.
* If you change the payoffs from 2⁄3 to 6⁄9, then there are no stragglers to kill. Or you could let the stragglers survive to to play next generation; if the population is large enough, this will not affect strategy.
I don’t understand what you mean by this.
Here, I believe you’re saying that you can pick a rate of growth in the payoffs such that, with probability 1, if everyone cooperates, then eventually one particular lineage (chosen randomly) comes to dominate to the extent that nobody else even gets selected to reproduce, and if the starting utility functions are all sufficiently long-term and risk-averse, they might prefer not to undergo that lottery. Is that right?
Your restatement of my example is correct, though the utility functions being long-term is not supposed to distinguish my example from yours. In a generational model where all the children happen at a predetermined time, discounting is not an issue. Your example seems to say that the agents care about the number of children (not descendents) that they have, regardless of when they occur. If they care about their infinite descendents they need discounting to get a finite number. If they care about exponentially discounted children, even with your payoffs and linear utility, they might choose to defect if the discount rate is high enough.
My version is exaggerated so that the question is whether an agent gets to play the game at all. With the original constant payoffs, every agent gets put in some triple (with probability 1), so a homogeneous population of TDT agents cooperate. Now go back to your payoffs and consider a mix of TDT and defectors with Omega doing the triples one at a time. The only interesting strategy question for the TDT agent is whether to cooperate against 1 defector or to act cliquey. To decide the expected utility of a strategy, the agent must compute the probability of the different triples it might encounter. These depend on the population when it gets picked, which depend on the strategy it chose. In order to answer exercise 1, it must do exercises 2-4 and more. It is unlikely to encounter the asymptotic population, but it is also unlikely to encounter the original population.
Here’s a rough calculation. Let’s start with 1 defector. Let’s assume that it encounters 2 of the original agents, not their descendents. Let’s further assume its immediate children encounter original agents, not descendents (a quite unreasonable assumption); and that they don’t get picked together, but face 2 TDT agents. Then the difference between cooperating and acting cliquey is 3 encounters with a defector against 9 such encounters. The number of children lost to such an encounter (compared to 3 TDTs) is 5 or 6, depending on cooperating or acting cliquey, which is quite large compared to the 1 that is gained by cooperating rather than acting cliquey. The assumption is ridiculous and the answer with linear utility is probably to cooperate, but it requires calculation and depends on the utility function (and maybe the initial population).