Template:Clobenefitfunc: Difference between revisions

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Created page with "; <tt>--benefitfcn <f1[,f2[...]]></tt> : benefit function for each trait: :; <tt>0:</tt> B(x,y)=b0 y :: benefits linear in opponents investment y. :; <tt>1:</tt> B(x,y)=b0 y+b1 y2 :: benefits quadratic in opponents investment y. :; <tt>2:</tt> B(x,y)=b0y ::  -saturating benefits for opponents investment y :; <tt>3:</tt> B(x,y)=b0ln(b1 y+1) :: ln-saturating benefits for opponents investment y :; <tt>4:<..."
 
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:; <tt>32:</tt> B(x,y)=b0x+b1 x2+b2 x3
:; <tt>32:</tt> B(x,y)=b0x+b1 x2+b2 x3
:: benefits cubic in own investments x.
:: benefits cubic in own investments x.
; <tt>--benefitparams <b0>[,<b1>[...[;<b'0>[,<b'1>[...]]]]]
; <tt>--benefitparams <b0>[,<b1>[...[;<b'0>[,<b'1>[...]]]]]</tt>
: parameters bi for benefit function of each trait.
: parameters bi for benefit function of each trait.

Latest revision as of 12:26, 13 October 2023

--benefitfcn <f1[,f2[...]]>
benefit function for each trait:
0: B(x,y)=b0 y
benefits linear in opponents investment y.
1: B(x,y)=b0 y+b1 y2
benefits quadratic in opponents investment y.
2: B(x,y)=b0y
 -saturating benefits for opponents investment y
3: B(x,y)=b0ln(b1 y+1)
ln-saturating benefits for opponents investment y
4: B(x,y)=b0(1exp(b1 y))
exp-saturating benefits for opponents investment y
10: B(x,y)=b0(x+y)
benefits linear in joint investments x+y.
11: B(x,y)=b0(x+y)+b1 (x+y)2
benefits quadratic in joint investments x+y (default).
12: B(x,y)=b0x+y
 -saturating benefits for joint investments x+y
13: B(x,y)=b0ln(b1 (x+y)+1)
ln-saturating benefits for joint investments x+y
14: B(x,y)=b0(1exp(b1 (x+y)))
exp-saturating benefits for joint investments x+y
20: B(x,y)=b0x+b1 y+b2 x y
benefits linear in investments x and y as well as cross term xy.
30: B(x,y)=b0x
benefits linear in own investments x.
31: B(x,y)=b0x+b1 x2
benefits quadratic in own investments x.
32: B(x,y)=b0x+b1 x2+b2 x3
benefits cubic in own investments x.
--benefitparams <b0>[,<b1>[...[;<b'0>[,<b'1>[...]]]]]
parameters bi for benefit function of each trait.