Score(s) calculations..

Zyxpsilon

Running Spider
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Oct 29, 2009
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As anyone should expect, the generic SCORE winning condition creates six types by stacking various amounts picked from Civs results/stats. I've been specifically curious what the 'Empire' line was exactly composed of & found the facts in.. the Scoring.XML (-duh) file. ;)

Sooooo...
--------------------------
<ScoringLineItems>
<Row LineItemType="LINE_ITEM_CIVICS" Name="LOC_LINE_ITEM_CIVICS_NAME" Category="CATEGORY_CIVICS"
Multiplier="2" ScaleByCost="true" Civics="true" TieBreakerPriority="100"/>
<Row LineItemType="LINE_ITEM_CITIES" Name="LOC_LINE_ITEM_CITIES_NAME" Category="CATEGORY_EMPIRE"
Multiplier="5" Cities="true" TieBreakerPriority="90"/>
<Row LineItemType="LINE_ITEM_DISTRICTS" Name="LOC_LINE_ITEM_DISTRICTS_NAME" Category="CATEGORY_EMPIRE"
Multiplier="3" Districts="true" TieBreakerPriority="80"/>
<Row LineItemType="LINE_ITEM_POPULATION" Name="LOC_LINE_ITEM_POPULATION_NAME" Category="CATEGORY_EMPIRE"
Multiplier="1" Population="true" TieBreakerPriority="70"/>
<Row LineItemType="LINE_ITEM_GREAT_PEOPLE" Name="LOC_LINE_ITEM_GREAT_PEOPLE_NAME" Category="CATEGORY_GREAT_PEOPLE"
Multiplier="3" GreatPeople="true" TieBreakerPriority="60"/>
<Row LineItemType="LINE_ITEM_RELIGION" Name="LOC_LINE_ITEM_RELIGION_NAME" Category="CATEGORY_RELIGION"
Multiplier="2" Religion="true" TieBreakerPriority="50"/>
<Row LineItemType="LINE_ITEM_TECHS" Name="LOC_LINE_ITEM_TECHS_NAME" Category="CATEGORY_TECH"
Multiplier="2" ScaleByCost="true" Techs="true" TieBreakerPriority="40"/>
<Row LineItemType="LINE_ITEM_WONDERS" Name="LOC_LINE_ITEM_WONDERS_NAME" Category="CATEGORY_WONDER"
Multiplier="5" ScaleByCost="true" Wonders="true" TieBreakerPriority="30"/>
</ScoringLineItems>
---------------------------

Mainly, what we want are each of the bolded "Multiplier" values above!

Then -- EMPIRE == Cities (5) + Districts (3) + Population (1)... these are per instances, 2 cities equals 10 points, every districts give 3 (I now think that's how AI constantly gets their high numbers!!), etc.

Worth noting are the TieBreakerPriority parameters which apply scaling mechanics to determine who leads for TOTAL classification.

Anything else is self-explanatory.
 
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