Command line

ljos-consensus settle [FLAGS]

Flag	Meaning
--issue ID	ballots from vissue vote ID --json
--ballots JSON	[{agent, choice}], or an object with ballots, votes or agents[].voted
--trust JSON	[[from, to, weight], ...] or [{from, to, weight}, ...]
--self-weight W	the diagonal when a row does not name it; default 0.5
--susceptibility S	1 is DeGroot; below 1 anchors each voter to its ballot; default 1
--susceptibility-of JSON	\{agent: s\}, a persona’s own anchor per voter
--epsilon E [--epsilon-of JSON]	bounded confidence instead of the trust graph: each voter averages only voters within L1 distance E of its own opinion
--max-iter N, --tol T	the fixed-point budget; defaults 200 and 1e-9
--seldon [--out DIR]	write Seldon inputs, run seldon, read the result

Output: options sorted, shares in that order, rounds, settled, engine (degroot-fj, bounded-confidence, seldon, or empty), polarization (the sum over voters of the squared distance from the mean final opinion) and disagreement (the sum over trust edges of weight times the squared distance between the two ends), both after Musco, Musco and Tsourakakis (doi:10.1145/3178876.3186103).

ljos-consensus surprising (--issue ID | --ballots JSON) --predictions JSON

The surprisingly popular answer (Prelec, Seung and McCoy, doi:10.1038/nature21054). --predictions is an array of {agent, expect} where expect is an option, or an object of option to the share the voter expects the others to give it. Output: options, actual and predicted shares, surprise (actual minus predicted), answer (the largest surprise; absent below two predictors), predictors.

ljos-consensus reputation --trust JSON [--agents a,b,c] [--alpha A]

EigenTrust (Kamvar, Schlosser and Garcia-Molina, doi:10.1145/775152.775242): a global standing per voter from the pairwise rows, the principal eigenvector of the row-normalised trust matrix pulled toward a uniform pre-trust by alpha (default 0.15). Output: standing as an object of voter to a share of one.

ljos-consensus reliability (--items JSON | --project P) [--rounds N]

Dawid and Skene’s estimate (doi:10.2307/2346806) of each voter’s accuracy from many items with no known truth: expectation maximisation over the items’ hidden answers and the voters’ accuracies, twenty rounds by default. --items is a JSON array of ballot arrays; --project reads every issue of a tracker project that holds two or more ballots. Output: items, rounds, and accuracy as an object of voter to a value in (0, 1), Laplace smoothed so no voter reaches a certainty.

The step

x(t+1) = (1 - s) x(0) + s W x(t), with W the row-stochastic trust matrix and s the susceptibility. A voter’s opinion is a distribution over the options, one-hot at the start. Missing self weight is filled with --self-weight; a voter with no row of its own listens to everyone equally, itself included. Shares are the column sums of the fixed point, normalised.

Library

The crate root exports Ballot, Outcome, roster, influence_matrix, settle, settle_anchored, settle_bounded, dawid_skene, surprisingly_popular, eigentrust, ballots_from_json, trust_from_json, anchors_from_json, predictions_from_json, and settle_seldon. The Seldon module writes and reads the engine’s files and links nothing under a copyleft licence.