Theory of Games and Economic Behavior
Theory of Games and Economic Behavior is written by mathematician John von Neumann and economist Oskar Morgenstern and became the groundbreaking text that created the research field of game theory. It is considered the classic work upon which modern-day game theory is based.
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- The original: Theory of Games and Economic Behavior, published in 1944 by Princeton University Press, by John von Neumann and Oskar Morgenstern the text that created the interdisciplinary research field of game theory, is still worth reading.
- Saying that von Neumann was one of the first game theorists undersells it.
He wrote the original book on game theory! The Theory of Games and Economic Behavior with Oskar Morgenstern.
Relatedly, MAD was his conception as well.
- > Where is the proof?
von Neuman proved it for 2 players in his classic "Theory of Games and Economic Behavior": https://archive.org/details/in.ernet.dli.2015.215284/page/n3...
Nash proved it for n-players: https://pmc.ncbi.nlm.nih.gov/articles/PMC1063129/pdf/pnas015...
> "GTO" is only possible against perfect play to begin with
This is a very common misconception, probably because GTO is usually explained as the equilibrium reached by 2 perfect players. The key insight of GTO is that you do not adjust your strategy to what your opponent is doing. If you play the equilibrium strategy and they don't, you're guaranteed to make money.
> And I also never claimed exploitative strategies guarantee everything, for the same reason "GTO" doesn't either. It's a game of incomplete information.
I didn't say you did, I was just making my own independent argument as to why intuitive play is dangerous and people often end up deceiving themselves into thinking they're winning players.
> And, there are pros that have been winning for long amounts of time knowing zero about GTO theory.
Which is why I said that, IMO, 90% of pro players fundamentally misunderstand poker (and that's not even counting the losing players who think they're "pro").
- > Which first-time founders do you think Paul Graham or Keith Rabois would more likely fund: Those who aspire to solve a problem with the world that they care passionately about?
It is worth reflecting on the fact that the founder of OpenAI has had the strongest possible endorsement from Paul Graham. He was claimed to be among the greats before his successes: Paul Graham put him among Steve Jobs and Elon Musk. When Paul Graham stepped down from YCombinator, he was so convinced of Sam's skills that he put Sam in his place. Later Sam started OpenAI.
> I would advise deeper thought into these topics when convenient. Read Nick Bostrom’s Superintelligence book or watch his talks, at least one of which was at Google HQ.
I've read Superintelligence, the Sequences, PAIP, AIMA, Deep Learning, Reinforcement Learning, and Theory of Games and Economic Behavior, taken a course in control theory, and read a book about evolutionary algorithms. I've also built systems after having understood these techniques for literally each of these things I've mentioned with the exception of all of Superintelligence and much of the Sequences with the exception of parts of the sequences which dealt with Bayesian reasoning, which I did implement and like, though I disagree with that community about its optimality because the conditions of ledger arguments aren't true in the real world. In practice, Bayesian approaches are like trying to build a sportscar for a race - you get beaten even though you are doing the fastest thing, because the fastest thing isn't as fast as the slower methods.
Anyway, the combinatorics of multi-step multi-agent decision problems implies a lot of problems for Bostrom and Yudowsky positions on the limits of what intelligence can hope to achieve. I don't find them to be the most formidable thinkers on this subject. In the case of Yudowsky, he admits this, saying that he finds Norvig to be more formidable than he is. And Norvig disagreed with him on AI risk in exactly the context I also disagree and for the same reason I disagree. To ensure you get the point I'll speak in terms of Bostrom's analogies: notice, there is, in fact, a speed limit. The speed of light. Well, what Norvig notices, and what I also notice, and what Bellman noticed when he coined the term combinatorial explosion, is that intractability is an actual issue that you need to confront. It isn't something you can hand wave away with analogy. We don't have enough atoms in our universe.
This is why we get dual mode systems by the way. Not just humans: notice, it happens in chess engines too. The general solvers provides the heuristic which must have error, then the specific solver uses the heuristic to improve, because it is in a more specific situation. Most of the people in the AI risk camp are pretty Yudowskian. They dwell for long periods of time on the overcoming of the biased heuristic. For sure, this makes them more intelligent, but it misinforms them when they try to make inference about general intelligence informed on the tractability in specific situations. It is because, not despite, the intractability that they find such evidence of tractability.
- Did you read it? They do mention Morgernstern multiple times in the article. Morgernstern's name is mentioned 10 times in the article. For instance:
>"This is most evident in his treatment of von Neumann’s pioneering work in the social sciences, the 1944 book Theory of Games and Economic Behavior, written in collaboration with the economist Oskar Morgenstern."
- They didn't, though. Look at von Neumann and Morganstern's "Theory of Games and Economic Behavior". There's nothing in there about time-series averages. It's a theory of games that you might play only once.
