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In their article, 'That is not dead which can eternal lie: the aestivation hypothesis for resolving Fermi's paradox', Sandberg et al. try to explain the Fermi paradox (we see no aliens) by claiming that Landauer's principle implies that a civilization can in principle perform far more ( ∼ 10 30 times more) irreversible logical operations (e.g., error-correcting bit erasures) if it conserves its resources until the distant future when the cosmic background temperature is very low. So perhaps aliens are out there, but quietly waiting. Sandberg et al. implicitly assume, however, that computer-generated entropy can only be disposed of by transferring it to the cosmological background. In fact, while this assumption may apply in the distant future, our universe today contains vast reservoirs and other physical systems in non-maximal entropy states, and computer-generated entropy can be transferred to them at the adiabatic conversion rate of one bit of negentropy to erase one bit of error. This can be done at any time, and is not improved by waiting for a low cosmic background temperature. Thus aliens need not wait to be active. As Sandberg et al. do not provide a concrete model of the effect they assert, we construct one and show where their informal argument goes wrong. [ABSTRACT FROM AUTHOR]

We study the equilibrium behavior of informed traders interacting with market scoring rule (MSR) market makers. One attractive feature of MSR is that it is myopically incentive compatible: it is optimal for traders to report their true beliefs about the likelihood of an event outcome provided that they ignore the impact of their reports on the profit they might garner from future trades. In this paper, we analyze non-myopic strategies and examine what information structures lead to truthful betting by traders. Specifically, we analyze the behavior of risk-neutral traders with incomplete information playing in a dynamic game. We consider finite-stage and infinite-stage game models. For each model, we study the logarithmic market scoring rule (LMSR) with two different information structures: conditionally independent signals and (unconditionally) independent signals. In the finite-stage model, when signals of traders are independent conditional on the state of the world, truthful betting is a Perfect Bayesian Equilibrium (PBE). Moreover, it is the unique Weak Perfect Bayesian Equilibrium (WPBE) of the game. In contrast, when signals of traders are unconditionally independent, truthful betting is not a WPBE. In the infinite-stage model with unconditionally independent signals, there does not exist an equilibrium in which all information is revealed in a finite amount of time. We propose a simple discounted market scoring rule that reduces the opportunity for bluffing strategies. We show that in any WPBE for the infinite-stage market with discounting, the market price converges to the fully-revealing price, and the rate of convergence can be bounded in terms of the discounting parameter. When signals are conditionally independent, truthful betting is the unique WPBE for the infinite-stage market with and without discounting. [ABSTRACT FROM AUTHOR]

In standard belief models, priors are always common knowledge. This prevents such models from representing agents’ probabilistic beliefs about the origins of their priors. By embedding standard models in a larger standard model, however, pre-priors can describe such beliefs. When an agent’s prior and pre-prior are mutually consistent, he must believe that his prior would only have been different in situations where relevant event chances were different, but that variations in other agents’ priors are otherwise completely unrelated to which events are how likely. Due to this, Bayesians who agree enough about the origins of their priors must have the same priors. [ABSTRACT FROM AUTHOR]

In July 2003, the Policy Analysis Market (PAM) was described as terrorism futures, and immediately cancelled. While PAM was not in fact designed to be terrorism futures, I here consider five design issues with implementing and using real terrorism futures: combinatorics, manipulation, moral hazard, hiding prices, and decision selection bias. As neither these nor other problems seem insurmountable, terrorism futures appears to be a technically realistic possibility. [ABSTRACT FROM AUTHOR]

Compared with non-union workers, union workers take more of their compensation in the form of insurance. This may be because unions choose democratically, and democratic choice mitigates adverse selection in group insurance. Relative to individually-purchased insurance, we show that group insurance chosen by an ideal profit-maximizing employer can be worse for every employee, while group insurance chosen democratically can be much better. The reason is that democracy can fail to represent the preferences of almost half the group. [ABSTRACT FROM AUTHOR]

In Everett's many worlds interpretation, quantum measurements are considered to be decoherence events. If so, then inexact decoherence may allow large worlds to mangle the memory of observers in small worlds, creating a cutoff in observable world size. Smaller world are mangled and so not observed. If this cutoff is much closer to the median measure size than to the median world size, the distribution of outcomes seen in unmangled worlds follows the Born rule. Thus deviations from exact decoherence can allow the Born rule to be derived via world counting, with a finite number of worlds and no new fundamental physics. [ABSTRACT FROM AUTHOR]

Consider two agents who want to be Bayesians with a common prior, but who cannot due to computational limitations. If these agents agree that their estimates are consistent with certain easy-to-compute consistency constraints, then they can agree to disagree about any random variable only if they also agree to disagree, to a similar degree and in a stronger sense, about an average error. Yet average error is a state-independent random variable, and one agent's estimate of it is also agreed to be state-independent. Thus suggests that disagreements are not fundamentally due to differing information about the state of the world. [ABSTRACT FROM AUTHOR]

Information markets are markets created to aggregate information. Such markets usually estimate a probability distribution over the values of certain variables, via bets on those values. Combinatorial information markets would aggregate information on the entire joint probability distribution over many variables, by allowing bets on all variable value combinations. To achieve this, we want to overcome the thin market and irrational participation problems that plague standard information markets. Scoring rules avoid these problems, but instead suffer from opinion pooling problems in the thick market case. Market scoring rules avoid all these problems, by becoming automated market makers in the thick market case and simple scoring rules in the thin market case. Logarithmic versions have cost and modularity advantages. After introducing market scoring rules, we consider several design issues, including how to represent variables to support both conditional and unconditional estimates, how to avoid becoming a money pump via errors in calculating probabilities, and how to ensure that users can cover their bets, without needlessly preventing them from using previous bets as collateral for future bets. [ABSTRACT FROM AUTHOR]

Focuses on consensus-inducing knowledge properties, relatively direct and precise functions of or bounds on the numerical values of individual estimates. Assessment of these functions; Significance of these functions; Requirements of the functions.