1 module PMDefaults where
5 import qualified NaiveMinCostFlow
6 import qualified CS2MinCostFlow
8 pmDefaults = PMConfig {
10 -- Choose a min-cost flow implementation (timings on mattlaptop2):
12 -- A naive implementation that is slow for all but the smallest instances
13 -- (30s on a 20x50 example).
14 minCostFlow = NaiveMinCostFlow.minCostFlow,
16 -- Uses CS2 (http://www.igsystems.com/cs2/), which requires a license for
17 -- non-research use but is faster (<1s on a 20x50 example, 64s on a 60x500
18 -- example). Configure the path to cs2.exe in CS2MinCostFlow.hs.
19 --minCostFlow = CS2MinCostFlow.minCostFlow,
21 reviewsEachProposal = 3,
23 prefIsExpert = \p -> p <= 10,
24 prefIsKnowledgeable = \p -> p <= 20,
26 prefIsBoring = \p -> p > 15,
27 prefIsVeryBoring = \p -> p > 25,
29 prefIsConflict = \p -> p >= 40,
31 -- For now this is absolute. Later it might be proportional to a reviewer's
35 -- Cost to overload by one review.
36 -- tx = 0 at target load, 1 at end of tolerance.
37 marginalLoadCost = \tx -> 1000 + tx*1000,
39 -- Cost to review a boring (or very boring) proposal.
40 -- lx = 0 at no load, 1 at target load.
41 marginalBoringCost = \lx -> 1000 + lx*1000,
42 -- Additional cost to review a very boring proposal.
43 marginalVeryBoringCost = \lx -> 1000 + lx*1000,
45 -- Cost to make a review.
46 -- I'm using quadratic cost functions as a first attempt.
47 assignmentCost = \pref -> (numAsWt 10 + pref) ^ 2,
49 -- Bonus for a first knowledgeable or expert review.
50 knowledgeableBonus = 1000,
52 -- Bonus for an additional expert review.