arXiv subjects

Robin Hanson

Publications and source records attributed to Robin Hanson.

5 recordsLinked to original sources

arXiv2021

If Loud Aliens Explain Human Earliness, Quiet Aliens Are Also Rare

If life on Earth had to achieve n 'hard steps' to reach humanity's level, then the chance of this event rose as time to the n-th power. Integrating this over habitable star formation and planet lifetime distributions predicts >99% of advanced life appears after today, unless n<3 and max planet duration <50Gyr. That is, we seem early. We offer this explanation: a deadline is set by 'loud' aliens who are born according to a hard steps power law, expand at a common rate, change their volumes' appearances, and prevent advanced life like us from appearing in their volumes. 'Quiet' aliens, in contrast, are much harder to see. We fit this three-parameter model of loud aliens to data: 1) birth power from the number of hard steps seen in Earth history, 2) birth constant by assuming a inform distribution over our rank among loud alien birth dates, and 3) expansion speed from our not seeing alien volumes in our sky. We estimate that loud alien civilizations now control 40-50% of universe volume, each will later control ~10^5 - 3x10^7 galaxies, and we could meet them in ~200Myr - 2Gyr. If loud aliens arise from quiet ones, a depressingly low transition chance (~10^-4) is required to expect that even one other quiet alien civilization has ever been active in our galaxy. Which seems bad news for SETI. But perhaps alien volume appearances are subtle, and their expansion speed lower, in which case we predict many long circular arcs to find in our sky.

q-bio.OT↗

arXiv2019

Comment on 'The aestivation hypothesis for resolving Fermi's paradox'

In their article [arXiv:1705.03394], '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 (${\sim} 10^{30}$ 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.

physics.pop-ph↗

arXiv2014

Trade-based Asset Model using Dynamic Junction Tree for Combinatorial Prediction Markets

Prediction markets have demonstrated their value for aggregating collective expertise. Combinatorial prediction markets allow forecasts not only on base events, but also on conditional and/or Boolean combinations of events. We describe a trade-based combinatorial prediction market asset management system, called Dynamic Asset Cluster (DAC), that improves both time and space efficiency over the method of, which maintains parallel junction trees for assets and probabilities. The basic data structure is the asset block, which compactly represents a set of trades made by a user. A user's asset model consists of a set of asset blocks representing the user's entire trade history. A junction tree is created dynamically from the asset blocks to compute a user's minimum and expected assets.

cs.GT↗

arXiv2012

Probability and Asset Updating using Bayesian Networks for Combinatorial Prediction Markets

A market-maker-based prediction market lets forecasters aggregate information by editing a consensus probability distribution either directly or by trading securities that pay off contingent on an event of interest. Combinatorial prediction markets allow trading on any event that can be specified as a combination of a base set of events. However, explicitly representing the full joint distribution is infeasible for markets with more than a few base events. A factored representation such as a Bayesian network (BN) can achieve tractable computation for problems with many related variables. Standard BN inference algorithms, such as the junction tree algorithm, can be used to update a representation of the entire joint distribution given a change to any local conditional probability. However, in order to let traders reuse assets from prior trades while never allowing assets to become negative, a BN based prediction market also needs to update a representation of each user's assets and find the conditional state in which a user has minimum assets. Users also find it useful to see their expected assets given an edit outcome. We show how to generalize the junction tree algorithm to perform all these computations.

cs.AI↗

arXiv2003

Drift-Diffusion in Mangled Worlds Quantum Mechanics

In Everett's many worlds interpretation, where quantum measurements are seen as decoherence events, inexact decoherence may let large worlds mangle the memories of observers in small worlds, creating a cutoff in observable world size. I solve a growth-drift-diffusion-absorption model of such a mangled worlds scenario, and show that it reproduces the Born probability rule closely, though not exactly. Thus deviations from exact decoherence can allow the Born rule to be derived in a many worlds approach via world counting, using a finite number of worlds and no new fundamental physics.

quant-ph↗