请问 我现在希望设计海龟死后他的财产可以以一定的比例留给后代。这些海龟如果代表的是穷人则它死后(年龄大预期值)会生出3个孩子,其生前的财产的90%均分给其孩子。若海龟是富裕的,其死后有随机1~2个孩子,财产已70%均分。请问大家如果加到下述程序中怎么实现1 m& k s' `5 @3 ^8 s. e( a
globals
- L2 T5 P+ i: N[
/ l1 o. f! D6 p; u3 {* K max-grain ( r; r2 y$ B, ^: B+ |
* l& t7 D- x, z& a R4 L: u) l4 {: B
]
8 g2 O+ d) G/ x: R# N/ T
; u2 O' v* k9 _$ Ppatches-own% ?7 v1 V+ k9 d) t
[ H2 E# N" G7 b) z5 }) n
grain-here 8 Z5 l3 p/ U$ M, H4 _; u" P) p
max-grain-here
# W4 h8 `- j7 F% u2 w]3 `6 j* x6 ~& c
8 T" D- g6 e& A3 N5 o$ {7 ^
turtles-own
( \) I- e; Q) R+ B[
; r7 k8 m; b3 R, W4 }' F) s age , X' S) y- F! U4 M& E2 X
wealth 0 P/ K$ @- T" X7 j8 g
life-expectancy
0 i$ ?, g$ B. F& L! u( { metabolism
$ S2 m1 `' _0 n3 F0 o2 y: q vision
F. v1 Z+ v5 i7 _ inherited . d8 k3 T8 e. @& f2 o
]
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0 H: d* ?- S* v$ ^to setup, T4 [8 t- |- k4 r6 L
ca
w+ M9 q& `; T i9 ?% x! b8 _ set max-grain 50
( m0 y8 X3 U4 B setup-patches4 h1 f/ O7 ]$ n% p b6 N
setup-turtles
& I$ d% Y% @0 z setup-plots
7 n1 f3 n/ ~- U7 o update-plots- l F. }% V+ k' E; V7 X8 f
end# M o1 U* Y( v- d$ d
to setup-patches
& Q4 v- Q/ `& L1 x) X# P ask patches: j" t; ?0 w: e6 Y
[ set max-grain-here 0
0 e. {! c% _- m& w+ C& v if (random-float 100.0) <= percent-best-land' O) C) r) k% T8 V6 T, X9 p
[ set max-grain-here max-grain& m& P& l; v6 o" r m
set grain-here max-grain-here ] ]6 a$ q0 H+ B( e1 ^+ o
repeat 5
2 i |; Z( Z! l, m; K) P [ ask patches with [max-grain-here != 0]
. r- j4 y1 M! \$ I9 w0 q, r [ set grain-here max-grain-here ]
" Z/ g+ ]* }, L( v4 ?+ ^ diffuse grain-here 0.5 ]
+ h: E6 o; o d) d% ?% A! q3 l repeat 10( k3 \5 m; x2 i
[ diffuse grain-here 0.5]
2 @2 i; D3 C6 V/ T. O0 {3 a ask patches. Q' Q4 O* O9 a9 ]8 x9 k9 Y1 n
[ set grain-here floor grain-here # l& F* k( B I7 Y% h5 u1 ?6 {
set max-grain-here grain-here
0 f) B. A6 y/ O8 Z4 L/ q! _( S recolor-patch ]) G3 s' z- q+ m5 Q7 g
end! z, E8 ] |5 ~& B& ^& E( Q3 }
to recolor-patch 8 `' b) O5 |; A; a1 D/ Z
set pcolor scale-color sky grain-here 0 max-grain7 {% h5 o. d7 i1 I' h
end( Y- \7 p6 T2 j" A+ m0 E
to setup-turtles
r6 }2 j( d2 a. t set-default-shape turtles "person" x% S: K' C- g a( D
crt num-people. f: E, W! J& k1 H0 ~1 ]: L% m0 J
[ move-to one-of patches & G; Q. L4 }2 m3 D
set size 1.5 ; C+ ~) y8 ?4 S2 z& {0 P5 J/ T7 E
set-initial-turtle-vars-age, z+ R4 V' ?. D( [7 f* A
set-initial-turtle-vars-wealth
* f! ^% t; Y% |( R set age random life-expectancy ]3 V8 h `+ d$ q8 A# R6 P
recolor-turtles# \8 y2 s" r$ J. ]. N' _. f
end3 I6 z; ]8 I! p
* L, m v9 k7 A6 y) }5 h
to set-initial-turtle-vars-age
0 X" Y/ q6 G* t3 \! M2 Z let max-wealth max [wealth] of turtles
6 p8 @, k$ p; V: T$ ]# k
0 m. e) ?5 \9 N+ e f ifelse (wealth <= max-wealth / 3)" y1 x3 b a, | t) b; U+ {
[ set color red ( ^& J) A, ]8 s( w( l
set age 0
, @2 Z; Z, @6 H7 n3 W, h: T+ @8 c face one-of neighbors4
" _; u. ]" ~: F9 j set life-expectancy life-expectancy-min +
- z3 ?' }. x% V. i4 H) ` random life-expectancy-max : b; Y: D( G) {9 v Z
set metabolism random 1 + metabolism-low
" C5 L. P0 @$ F# R9 v set wealth metabolism + random 30
0 @0 V. B+ }3 q6 R7 F3 k9 q set vision 1 + random max-vision+ a& M6 o0 N4 e2 {* a
set wealth wealth + Wealth-inherited-low ]
' p$ ~+ r7 C( A' @& p4 _ [ ifelse (wealth <= (max-wealth * 2 / 3))
C. z% z5 V' }$ B% O) w [ set color yellow
9 v( V: ?7 I# T- a2 C b set age 0
/ r8 q! c" Y% }! _ face one-of neighbors4 9 J9 V, v) G' |# D) F7 V
set life-expectancy life-expectancy-min +. w9 ]2 b% ?% D. ]' |
random life-expectancy-max + 12 ~0 {$ Y1 G& v
set metabolism 1 + random metabolism-mid l( L. a4 [8 {. ^8 T) [6 A
set wealth metabolism + random 30- b7 r: A1 g1 e u: _% V1 [
set vision 3 + random max-vision
, m6 e# Q# X3 P* ]" @; ], i' [ set wealth wealth + Wealth-inherited-mid]% ]% W6 C9 ]! e' R- l ?7 l
[ set color green * V7 s6 B. \! V F
set age 0
& {- v2 g# Q' Y! a) l. p face one-of neighbors4
1 F6 O0 k' Y. V x+ Y! C, |, m set life-expectancy life-expectancy-min +7 C7 z1 y/ J3 l* G f8 R$ h2 }
random life-expectancy-max + 2: G; S3 b( |3 E
set metabolism 2 + random metabolism-up F4 m& t4 }5 b0 h' @
set wealth metabolism + random 30: r2 Y* Q3 F F% J! Z
set vision 3 + random max-vision
! s9 Q1 g, @( M, P set wealth wealth + Wealth-inherited-up ] ] # [0 ~& @1 r+ E+ g6 ?% C* n( b5 E6 v$ q
9 C* ?( z2 Y- B8 L' _
end
' f3 @" y; s- Y! Rto set-initial-turtle-vars-wealth G- r- d1 J0 r* u b. A9 z
let max-wealth max [wealth] of turtles
0 A3 N8 L+ Q7 y1 T) b4 Q set age 0
0 E$ r; e% H- ?( } face one-of neighbors4
5 T' h# p. Z2 t, k set life-expectancy life-expectancy-min ++ Y5 E& U% w3 i7 K! T6 Q1 [, v8 h/ W8 M
random life-expectancy-max
/ V8 h% _; |" H set metabolism 1 + random metabolism-up8 d& M4 c8 C* ~. R7 y: S$ [
set wealth metabolism + random 30
3 c5 e9 d {; o1 A! c% a# v set vision 1 + random max-vision
6 V; P Q- x7 m$ J: oend
) q8 k# ^" Q7 `; [3 O) ^% c" @to redistribution* R' h# m# T3 N
let max-wealth max [wealth] of turtles0 `0 E; o9 a) k) \9 [5 J& u
let min-wealth min [wealth] of turtles
' w! d- W1 `9 u; w+ pif (wealth <= max-wealth / 3)) @$ L; h* S; U
[set wealth wealth + Low-income-protection ]
' R0 d! h5 X! K5 M/ \$ p' oend$ P P$ D3 j" v" Q0 ^
* U. Y8 R% }' qto recolor-turtles
* @! |" E6 m; c. ]7 W2 T let max-wealth max [wealth] of turtles% ?' E. o2 M0 q' z
ask turtles
) B$ G6 g8 [$ d. m [ ifelse (wealth <= max-wealth / 3)
+ ]! p2 }6 q( j [ set color red ]6 g0 `/ C1 p* W0 J) M5 |
[ ifelse (wealth <= (max-wealth * 2 / 3))
; y* u5 d% F, c7 {9 r [ set color yellow ]8 i P# h8 D- d' b8 G* B! X. k
[ set color green ] ] ]
: U* t4 ]: v, a5 y% @, R ask turtles [ifelse show-wealth?
1 x" V1 E+ V1 Z& i: W+ b [ set label wealth ]
: J/ E) K+ S7 R9 H9 @+ T1 z [ set label "" ]]& w" O6 _- I0 l! p' p# O
end
4 }+ w" N0 ^" x& x) q0 j& ]% @3 A
to go
4 v' U$ V+ ^! {. y, A ask turtles% h1 }. ]8 J( l$ S% c$ x6 `
[ turn-towards-grain ] ; F6 ]2 V* H, w
harvest
6 a' U/ C$ H, r" s ask turtles8 L) ~. n6 d/ u
[ move-eat-age-die ]
1 W* i- J/ z* L) m8 h8 |- `, H recolor-turtles
! Y! H; _- w8 t2 U) a if ticks mod grain-growth-interval = 0
7 j1 B3 b( R" |. G0 ]& |' W( { [ ask patches [ grow-grain ] ]
7 O! ~- z1 b B) } 3 \8 Y8 x+ _2 q: Z
if ticks mod 11 = 00 Z3 ^' W" w2 _6 S
[ask turtles" x# U( q) `1 |3 J
[ redistribution ]]
6 ~5 ?& Y% ]3 j$ p. L3 U if ticks mod 5 = 0
; H2 r. b' N8 ^5 g [ask turtles! p6 M/ y6 J. G0 {# }0 P
[ visions ]]
3 @+ o* P/ Q `; W* M1 `- i8 C tick
7 Z2 f' p- e) b! g9 D4 S' F4 G update-plots
2 g% b& K0 x4 H; T! ^+ L9 `, f3 xend
6 @/ M6 \+ c, G1 J& T7 kto visions
- I# u9 [ y n set vision vision + 1
3 j1 [" b$ O9 W! y) U6 w1 n$ rend+ ]/ t ]- A/ Q9 ]5 x8 ~* B1 x, b
6 I/ ^, r# l, U) m3 T
* n7 m3 d- x. G, {, n3 B' a
* }9 M# h6 k1 ~+ ]3 l& {5 d7 u z: x7 cto turn-towards-grain
5 g% r9 t b% u- }; A5 z set heading 05 q$ h: Z. A5 U
let best-direction 07 R. p) v9 r& R `
let best-amount grain-ahead% [/ L1 I% Z/ x& l" F+ r* A7 o
set heading 90
, u/ y( ?7 W! w, r if (grain-ahead > best-amount)
8 S- W$ ?' L* f8 [( Z2 V8 W [ set best-direction 90
) V% R7 e( x" Y% C3 ]- U set best-amount grain-ahead ]
) P6 P. }) N/ h set heading 1803 D7 \8 n$ q8 z5 {
if (grain-ahead > best-amount)
8 H2 x/ ~( i/ U: W) R- N [ set best-direction 1802 c. b8 K, s2 G' X* h
set best-amount grain-ahead ]' B6 q1 P( ^' Y7 N9 E* d
set heading 270
3 C# {# l, L: a) ~; b$ z if (grain-ahead > best-amount)
5 |) s2 R' W$ i3 a L) P [ set best-direction 2705 w% i( ~. t% P4 w
set best-amount grain-ahead ]( |7 h; e4 w# @: {; E
set heading best-direction
4 t# }* U' [; p- t* i. M0 Tend/ G+ I* A6 z/ |. ?$ p
+ w/ T3 A5 Q, J! s v
) E+ _' g0 G$ a' t6 z, m3 p& Hto-report grain-ahead , M5 R* O0 R+ w3 G1 z4 D
let total 0
2 X0 j/ }; F& H ]3 |; w1 ~ let how-far 10 O4 Q6 L! d4 c0 X; W
repeat vision
3 |, n4 E% r; d$ A; F- A [ set total total + [grain-here] of patch-ahead how-far
g/ v0 Z1 l: s0 g2 b$ d; u, C8 o set how-far how-far + 1 ]7 q+ p7 D/ e( S1 b% b' \- Y$ J
report total$ P6 s& r+ ?7 g: p
end
( F: G' m7 T( U4 {6 h1 C! w8 n3 L! f7 \, v* O- b( P
to grow-grain
) B0 x5 t6 T( ?0 Q$ c- K1 B& O9 i/ u if (grain-here < max-grain-here)2 R! [# E6 o" a2 B/ ~4 T9 L
[ set grain-here grain-here + num-grain-grown
, R3 q+ \3 J, Q6 {- E) f2 P if (grain-here > max-grain-here) * c' X& p+ n' M
[ set grain-here max-grain-here ]
8 W/ \( A- u* _# I' l/ q) W Y6 _ recolor-patch ]" A7 j' Y# H$ G
end
" ^& u9 M' b, h6 P/ [" yto harvest* V9 R) Q* n% G. P# F6 u+ ^8 v
ask turtles
1 w4 ]4 t/ X7 U7 K W [ set wealth floor (wealth + (grain-here / (count turtles-here))) ], c" b1 K1 r3 x
ask turtles/ {" a; S& J! W7 z% o s7 X: p4 E
[ set grain-here 0
' |% m2 C: d i: \- A% g( \& l$ K* R recolor-patch ]
% r9 ?* _0 J5 n* ?: w
9 z" f( n/ t- R) Gend* {6 s: X6 |2 }1 F4 d; j1 A! s5 d
2 U( Z0 [: s$ O8 r1 B* A9 l
to move-eat-age-die 8 l/ F, Z1 Y5 H) D: C
fd 1
% t" s: t3 q! O) V/ g9 E8 b3 s" A" | set wealth (wealth - metabolism); @0 y+ t+ o0 c7 { u3 E: R' w$ @
set age (age + 1)
5 {# {+ H7 T# q, d8 E" u* o if (age >= life-expectancy)
7 j0 R; |1 V# q1 U9 D8 ~3 s [ set-initial-turtle-vars-age ]& H& E i6 j, q0 e- e% e
if (wealth < 0), B1 T u. u) @& ~8 \6 ]* O
[ set-initial-turtle-vars-wealth ]& P+ w, H$ H9 ^# @: u
" z, }9 f0 f: z7 h- W- N4 j
end
% F8 C. V4 S+ ^3 g& n/ c2 _9 _7 T7 q+ O
3 b' R; g' j* e6 b4 Rto setup-plots {+ i0 Y: ?; |* W" D% ~( H0 G
set-current-plot "Class Plot"* {& ?9 _+ ]' G3 @( w4 A( B
set-plot-y-range 0 num-people
0 M7 u) A! T2 M: ] h6 j% I% s set-current-plot "Class Histogram"# {* I4 m0 b5 b, j! Z4 H% X% N5 V
set-plot-y-range 0 num-people
7 w8 k4 v4 k0 j5 Y% H/ `! cend" l' \: \. V0 [; b. V1 q! }9 }+ T
# H* H) V7 a W* u( _
to update-plots
1 E; Z G2 \9 Y+ S* j z update-class-plot4 A+ a+ N7 I+ `* J( l
update-class-histogram/ r" ]3 U% ^; M' j" w$ y7 M/ l1 [
update-lorenz-and-gini-plots
$ t: L& v7 S, F" [7 W+ b* a* wend- v1 ^8 w( r% `% o- H+ s3 c) k
; \1 E, ]7 ~ d2 T: y8 v
to update-class-plot
) k6 _5 M! k! U" |% g' N+ C( ^ set-current-plot "Class Plot"- r8 u4 p9 x+ e; n! t( C& m! X {: C
set-current-plot-pen "low"/ h" f7 y# `* q+ a5 K
plot count turtles with [color = red]% a- N% @/ O7 ^; t3 x
set-current-plot-pen "mid"
$ Z: T2 k+ j4 M/ E# k) \* J plot count turtles with [color = yellow]
7 J2 f% V8 W" p s; N0 M set-current-plot-pen "up"
9 q# n; O; s4 ?6 E; t- J. X plot count turtles with [color = green]
! J+ C* D* f* ~end2 q+ ~) `9 R4 z/ }
4 B( h/ ^ S- w# ]9 D
to update-class-histogram
' Y0 p" y% o+ `) [. S4 V2 O9 ^ set-current-plot "Class Histogram"7 ~- ^9 W! Q9 A
plot-pen-reset
4 a2 u2 ^: N& X; o; T6 Z set-plot-pen-color red3 G3 q. J; A9 q: r/ Z3 L$ S
plot count turtles with [color = red]6 r# h8 A3 }* R7 n! M) P! ^" C( Q
set-plot-pen-color yellow+ ] `; M, p1 {$ Y; J
plot count turtles with [color = yellow]
1 E P9 \6 T- w$ _1 Q! C, }7 S set-plot-pen-color green
. E+ u0 O- N1 k' k3 | plot count turtles with [color = green]
4 }& t" m4 C8 ~- Gend
" L8 \6 B3 G7 K8 w+ }1 Lto update-lorenz-and-gini-plots
, w/ T2 ^2 V$ ] set-current-plot "Lorenz Curve"
; X* K \: g" H9 F clear-plot- r7 c, K! I5 l0 S
+ n, E8 u! q6 B9 r. }! Q [( \
set-current-plot-pen "equal"2 ?; U+ ]. U* P. y+ ?2 W! k
plot 0
! T$ W) A% y- f( s! x9 D6 K/ ` plot 100
$ o0 B/ K4 b, ?9 t4 @# a/ d& z8 K* s8 G
set-current-plot-pen "lorenz"
! ?% B+ j; ^( F" S& P: q set-plot-pen-interval 100 / num-people
; \9 r0 G5 H8 F1 r( x6 V plot 0( w$ h9 [) Y8 I( X
9 x M- n3 ?6 O/ n let sorted-wealths sort [wealth] of turtles
! E+ y- T+ }- s, o; R$ M. G let total-wealth sum sorted-wealths
" r { r$ C/ S5 k' [% s3 L let wealth-sum-so-far 0
* \: v5 p. @% [. z' q let index 09 \+ B6 l" \& j# z. T B+ K
let gini-index-reserve 06 H& z6 S g7 e9 C
* ]5 g# o0 j: Y6 \$ s, n* T' q repeat num-people [
+ e3 a; K& }% a7 c* `2 i set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
. d6 N$ a5 }1 d plot (wealth-sum-so-far / total-wealth) * 100 \3 D5 g1 E+ K
set index (index + 1)2 {3 f. K4 ?: G9 c. F2 s' M9 P
set gini-index-reserve9 ^1 r6 j) F. J v
gini-index-reserve +
0 [& t* D4 i/ g% H6 Q (index / num-people) -3 t7 [" ^ p& `5 a3 W
(wealth-sum-so-far / total-wealth) E9 e3 I& u' w* G0 x1 _/ T3 r z: v
], C6 E( d' h% g& y6 R
, y9 W( ^" R5 c A9 b! ~
set-current-plot "Gini-Index v. Time"
4 X6 M. c+ j. I: n _ plot (gini-index-reserve / num-people) / area-of-equality-triangle, T4 _% o2 [) |! M S8 q5 G
end
& Y' H. a q- Kto-report area-of-equality-triangle
3 c2 R! T/ }+ o report (num-people * (num-people - 1) / 2) / (num-people ^ 2) g8 j7 q8 B3 |% L+ I2 j
end |