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, Y: a: x+ D0 D% Z/ z' {7 a& u/ G# A2 V4 M
globals0 i; Z) f$ P; |& i
[' k" h7 ]: `/ ~) X @+ E
max-grain 7 [) Q+ R% O) Y
9 n* ]! @' l! O8 Q2 F; o
]& o) [" R) P- j
8 @) J9 I9 m0 Wpatches-own
6 S+ N2 Y0 x* J1 ~/ n# s; c* Y[4 O# {- U5 P' a& R- \4 b3 \
grain-here
. \% X. C" h8 G9 u2 j3 v8 `, Q/ O max-grain-here
6 P: i# c7 T" v t( t9 Y]
' U! |, [' w& T( |
; y- M" K- Y. K* tturtles-own y" A) o" b n( C# T
[; M3 @" V- M+ n! O
age - ~2 |1 A$ H( Y$ I% C5 W' B/ N
wealth ; Z6 h5 Z7 W7 v' M
life-expectancy
% Q W* ]) Z1 ]: _$ r metabolism
# A5 B; X U- H: r vision
+ n6 h6 M, n: |- l inherited ) ~8 h4 |5 r7 `2 _) s6 \
]
7 U2 t6 q5 H0 E3 `
; o S4 P4 }& h7 {6 k& w; S& C5 u; B; B) O, C* v
to setup
' |1 J# S9 q# i: y% y5 J& d# T ca# ^2 ?; |: |% `; \, t
set max-grain 50) {+ J/ b* t& }8 D8 L
setup-patches4 T* l6 I1 v4 {+ K+ {. d; ~( ]
setup-turtles6 u, q. _4 h$ {$ ^3 [
setup-plots- h8 \6 N. J- Q. m* R/ a2 C
update-plots e- P! t# R$ A0 P, m
end
9 H: U( o1 u6 Xto setup-patches
$ q( }/ h6 Y. C1 P6 s. B) t2 O ask patches
9 ]) G5 U; I+ e' V+ U [ set max-grain-here 0
7 D U# P& \* ]0 C6 C if (random-float 100.0) <= percent-best-land
3 k* t' @3 t3 E4 L3 m [ set max-grain-here max-grain
6 ?8 Z6 s* Z. p$ X: D set grain-here max-grain-here ] ]/ c* @' c3 u3 P2 E* X7 J4 [9 r5 C
repeat 5
: \+ c: W( r" r [ ask patches with [max-grain-here != 0]
* f8 S* J. Z5 I0 J" ?' g9 \. t [ set grain-here max-grain-here ]4 Y( d6 K" e0 \2 l+ P6 {
diffuse grain-here 0.5 ]
4 P4 H5 ^2 h2 {7 x repeat 10
, |7 D+ G* W0 H% P, t B [ diffuse grain-here 0.5] + \; {" d; t. _5 g/ e1 M
ask patches
# M: B( v+ _ w+ Z% \" a: B. M7 R [ set grain-here floor grain-here 4 b T. b, Q1 t+ s; l R
set max-grain-here grain-here
5 D; ^% ~8 N2 l# U* T$ A recolor-patch ]/ N. [- r% x& Q' F4 S
end* P, i+ {; ?# f4 E6 b
to recolor-patch 0 \3 r. M8 d) {- z z2 n# ]2 p) y6 n
set pcolor scale-color sky grain-here 0 max-grain' ]& z2 j( i% F. D
end
0 v+ f& w1 C6 R8 h3 }1 xto setup-turtles
8 j6 U+ ?% ?8 B5 ~; o set-default-shape turtles "person": n4 J! o, z: C( L( ~
crt num-people
+ Z3 Z, }( ?- u! y: K [ move-to one-of patches
+ V, n/ m3 v& E8 G/ @2 R- | set size 1.5
* a6 A" I6 q( \# k- D7 k set-initial-turtle-vars-age1 O B/ z1 c. u8 s8 d) t7 y
set-initial-turtle-vars-wealth% Z0 Z5 |; t- q" T7 ?
set age random life-expectancy ]( j8 j1 ]! G" {7 _+ e8 t' N8 U
recolor-turtles
- V; f8 m+ M& |$ h9 nend1 ^# U7 X8 r- m& e: f2 e% e8 D4 s
* C$ V5 q% E5 h
to set-initial-turtle-vars-age
% R/ Z5 r/ n$ }3 Z. F6 m; H3 F let max-wealth max [wealth] of turtles
5 I# T% ^1 l6 s # D m: L6 ?5 g `2 E. A8 \4 X
ifelse (wealth <= max-wealth / 3)
+ L9 Y; G) \/ F. {/ t6 {" r5 c, l4 k [ set color red
& E/ X8 K/ H) }2 s0 b/ V5 j8 v set age 0
: _) ^0 x' T& B% l5 d face one-of neighbors4 6 m; _4 W, ^ D" \6 _* f
set life-expectancy life-expectancy-min +; ?( K2 o' H5 B' A
random life-expectancy-max
{$ p7 d1 L' y$ b0 u7 @; O set metabolism random 1 + metabolism-low5 L6 |9 B( j) h9 X/ K- ~
set wealth metabolism + random 30
( e3 M. q" K( |1 a3 l6 Q+ X' R set vision 1 + random max-vision
! w& l1 K2 g4 s9 \" y T5 z set wealth wealth + Wealth-inherited-low ]
, h9 Y6 {4 ]# G: P, J1 N [ ifelse (wealth <= (max-wealth * 2 / 3))
% w7 c) V% }) n2 i) Q8 } [ set color yellow
. i8 ]" |0 x9 _: [. I5 G$ x* m set age 04 k' l) h, V& z8 m7 X
face one-of neighbors4
3 O0 P% H# ?4 \& l0 l% I set life-expectancy life-expectancy-min +7 j6 n; `5 Z' B# C& b3 X+ M `& m5 R
random life-expectancy-max + 1, A7 T" n# O3 ]5 o7 p
set metabolism 1 + random metabolism-mid
9 [+ i. o* T) i4 r& w+ D: d9 U6 w set wealth metabolism + random 309 t: e6 x( f" c; ^1 O
set vision 3 + random max-vision
* T0 ^' m6 ~2 c2 u9 L set wealth wealth + Wealth-inherited-mid]5 @3 N, ~9 S3 b. A, T; U
[ set color green : Y! e' m: g" y0 E$ M: V# i$ p3 ~' X9 D
set age 00 i' [ t" S% c: \
face one-of neighbors4
8 [4 a' f. {, q/ G. C& r z set life-expectancy life-expectancy-min +( D& ?/ A1 b0 s+ R
random life-expectancy-max + 2
5 C$ T) }, E* b+ p( o set metabolism 2 + random metabolism-up
; C) c* W& k" [& ^( C set wealth metabolism + random 30
% i) z4 G1 _( f+ R+ g+ W& S+ i set vision 3 + random max-vision
5 |, n2 E: L7 I8 N set wealth wealth + Wealth-inherited-up ] ] 1 {! g$ w2 M1 g+ U% \
4 w1 A# p. L4 a' w. B* a) x
end
! j R$ [, v7 f: l9 }* Hto set-initial-turtle-vars-wealth5 t2 P) P) g0 x. h! |
let max-wealth max [wealth] of turtles, ~+ B2 I- M1 F9 {$ l+ s$ P
set age 0
+ j" C& t: J1 m* J: O4 W, h, f face one-of neighbors4
1 e0 ]/ ~2 H3 z% q3 ? u6 a( J set life-expectancy life-expectancy-min +. r2 K) f9 \2 ?% s/ W/ A7 U
random life-expectancy-max
. w( d; x3 y) h$ u set metabolism 1 + random metabolism-up6 P% f' L+ L( n2 M
set wealth metabolism + random 30
3 U \# e; B {; @0 j* w. } set vision 1 + random max-vision 9 ?' b9 y& j+ @. q! w1 h
end A+ W' b% _; i' t# S
to redistribution5 x2 u) t$ H5 F4 t
let max-wealth max [wealth] of turtles9 e( s$ V, K# c/ I, F
let min-wealth min [wealth] of turtles
0 G6 |: z2 s0 \8 b5 L7 S2 mif (wealth <= max-wealth / 3)/ P! h2 L. J1 ~1 y$ t& G
[set wealth wealth + Low-income-protection ]
6 X9 s* L4 _3 P% d0 aend
) O4 H5 [4 d g $ \0 p3 L: T$ M
to recolor-turtles4 \! q5 I" W& }/ q# U# t
let max-wealth max [wealth] of turtles
- v8 m( M( f1 q- ^2 o* [6 [1 H ask turtles
1 f/ G" w1 Y1 ?! ]/ p [ ifelse (wealth <= max-wealth / 3)! G ]! W( k) N* w- u
[ set color red ]2 v, K9 K0 K% Q6 d# K, k
[ ifelse (wealth <= (max-wealth * 2 / 3))
0 \* j1 b M9 O [ set color yellow ]- D2 `7 f. d7 w' l, U* @$ N m
[ set color green ] ] ]
# `- z4 m3 d0 Y- N: M" P1 c0 J5 F) \ ask turtles [ifelse show-wealth?
' W# h% ^$ }: r; d2 K; E [ set label wealth ]5 Q9 Y& A# F2 ?5 F
[ set label "" ]]
2 p- J( M. J, U& M( P3 S7 N, Oend
$ m5 M" y Y- [; H$ F* n/ P& S4 p% l& S# D
to go
/ S" F/ \& r( f' o0 v, i ask turtles
% R+ F$ X. a/ { [ turn-towards-grain ]
! b4 c/ t! H$ |* A harvest; E% L8 j; f0 u! F5 i
ask turtles
( _: q/ b% c7 a8 z/ b* Z: W4 A [ move-eat-age-die ]
Y/ g/ C! J+ ]3 p6 i recolor-turtles' o z' q1 L4 ]* T2 I# A5 Q
if ticks mod grain-growth-interval = 0/ K# y7 w0 x: _ G( P# O
[ ask patches [ grow-grain ] ]; j; A K0 U& ]. n
8 l' G+ Q% b N8 X5 c if ticks mod 11 = 0
1 ^+ K3 d1 ]+ k* ~ L6 I [ask turtles3 h1 R, `& N3 o. N: R
[ redistribution ]]
7 N. M: e& h9 m n& X if ticks mod 5 = 0& p& U1 ^& Y3 j* k+ n( s7 _' A
[ask turtles8 z |: i+ g; P8 u/ b& }5 ~) I& S
[ visions ]]
- r: w. s+ J9 ]8 ]) D, ]" e tick6 p) |4 ^- V) \- d( D5 R. r) I
update-plots
( p5 i3 Z. z9 Z/ ?end8 D! d# q4 m' F/ A( T; J
to visions
! D" \7 M5 t2 ?& i2 n2 F set vision vision + 1
) P! q) g0 ~2 A$ t3 y# R: |$ vend G, K3 [: i1 V6 P- j
6 D) J, V) r# O! i4 c% i- q: L* g) z2 t- j$ x$ m
+ N6 \3 X% q9 ]! `' k' N
to turn-towards-grain " A) w% w9 x6 `; _& V
set heading 0
* A2 o1 x3 O$ @7 K' e let best-direction 06 `9 ~; G( x. z5 Q- ^
let best-amount grain-ahead
# J' ?8 Y" n5 c' X% x set heading 90* {2 d. x0 m: L% g2 I: k
if (grain-ahead > best-amount)
( y# z7 ^. S. F [ set best-direction 90$ E# A. f4 S+ o
set best-amount grain-ahead ]
' A: G6 y/ [" @* g# {5 S set heading 180
# @) W8 S$ ?/ p! T3 C/ d if (grain-ahead > best-amount)% u" b2 s. ]% f2 o0 M" ^0 {9 s
[ set best-direction 180
0 U* v- F9 T& J4 i$ F3 j set best-amount grain-ahead ]1 a2 H8 z+ T" J/ G
set heading 270
5 b# X$ M8 A# S b if (grain-ahead > best-amount). ]$ ?& r& n& J( k
[ set best-direction 270 c$ j$ \0 {0 B
set best-amount grain-ahead ]
. y2 m* a) I- S8 C set heading best-direction
! z& [/ _" U# c, Iend0 f0 t+ D# u; d# @" D: F+ I9 y5 I' B* M
) @" f. G* h5 g% M( N
1 v4 ^1 ?/ N- x2 T6 \to-report grain-ahead / K m, H8 h8 _9 A
let total 0
8 z- f7 z9 X4 g- ?9 s, n7 h let how-far 1
# b0 j3 @. k2 h6 S! ]. k; j+ `/ g repeat vision O2 t6 f2 c+ B) x! i: {" ]; t Y
[ set total total + [grain-here] of patch-ahead how-far
3 W5 U2 ]. a z1 x$ I1 { set how-far how-far + 1 ]5 U' L+ \& O9 p' f4 Z( q
report total! m/ b7 [( K# ? X) W* i+ k
end* r2 B* I3 X. ^; J+ ?4 ]( E
( C" v9 p) o$ v; b X8 _to grow-grain
, H2 Y( F( M3 u. N) ` if (grain-here < max-grain-here)
7 c5 n* Y$ q1 V- q( W5 w2 k- g [ set grain-here grain-here + num-grain-grown
3 O" a. [3 i; n- ? if (grain-here > max-grain-here)
5 E6 f! i, N. ^: d1 ] o [ set grain-here max-grain-here ]8 f8 ], N# u& o3 j0 \
recolor-patch ]. K, D2 O2 R0 { I' F% I& J
end
( V1 `& v) I6 _2 g- B5 a: L' |5 C2 ^2 Pto harvest
" N* ~& `; Z- Q! L! e) M9 i ask turtles
) G" } i) G7 T, M0 t1 p9 o/ { C* X [ set wealth floor (wealth + (grain-here / (count turtles-here))) ]
- G4 N$ l, r- ^5 h3 Q ask turtles
" v* L" h; [; U8 ?- W% H$ j5 J- l [ set grain-here 0
& d, O; |* P% j) V* w3 p9 l- e Y recolor-patch ]2 k; h- }) y2 C( Z
# i3 B* N) T# P
end
, Q; J |4 W% i5 x6 A, J2 `$ B/ r9 q" B! f+ L
to move-eat-age-die
7 A# {! A6 P: C5 O fd 1$ p- j5 k4 x8 r5 x+ ]
set wealth (wealth - metabolism)
0 M# k& z$ e1 ?5 g& a/ U8 F set age (age + 1)5 ~2 j. Y9 \) k4 c6 S6 P
if (age >= life-expectancy)
, k: K. [5 H/ B4 Q) z! M. Q' _5 S [ set-initial-turtle-vars-age ]
" M5 S9 r; q" p; { if (wealth < 0)
! ]$ Z' ]9 {# i) u [ set-initial-turtle-vars-wealth ]
7 v1 I$ A d% P$ ?5 C 1 `, j) v4 _* ~9 q( G# f, i
end
$ E8 }6 F- C& y8 R- Q9 n& @/ t" B) j
/ h. z c! Y" u
& l+ \9 g- q/ h8 ^# Oto setup-plots; |; Z1 H2 q* q/ A1 _
set-current-plot "Class Plot"/ x/ b4 O* `& ?; l# V: s. ^
set-plot-y-range 0 num-people
+ w5 M" U% m, e9 G3 S set-current-plot "Class Histogram"/ g* Z: y$ T. b- i' n6 c" k
set-plot-y-range 0 num-people5 l! \, s& D F. Y# m# X
end
9 T- s" L Y( Y% I; ~
3 @5 w1 u6 J2 X: Dto update-plots
* D/ a% R M! n W4 m0 l update-class-plot% W* A7 @( L( _; |2 R* J
update-class-histogram2 W" V1 ^8 N: t! H1 m! O/ w
update-lorenz-and-gini-plots
; s$ E9 v. D2 A& m: d& Uend
; w" B$ W/ e# F" M% Y0 \* |9 e+ O
8 C9 o- `6 E: V" B. Zto update-class-plot% f$ K, d' Z0 C2 ]
set-current-plot "Class Plot". m8 m& U0 z) z4 l7 z
set-current-plot-pen "low"( y" |0 M/ G- ]8 T, ]
plot count turtles with [color = red]
% `9 I- P& w% f* Z; W1 @1 q set-current-plot-pen "mid"5 e" [$ {! k4 `
plot count turtles with [color = yellow]
. Z9 y" i, Z5 U& O. v set-current-plot-pen "up"
$ X8 ?8 Q0 m: ]; ?, k plot count turtles with [color = green]4 t$ f; W' l9 s7 C y5 H4 p. g
end
) I: _! f; @' w0 w5 V5 G% | L2 ?/ X/ r+ | H3 b
to update-class-histogram
; N2 E6 j5 ?6 Z set-current-plot "Class Histogram"
" o& c8 h3 Z' P" u8 d; R0 D plot-pen-reset" `" X9 \: {9 p
set-plot-pen-color red
! v% v$ S6 x+ L: P5 p plot count turtles with [color = red]
) {1 k( |1 w- _* c8 q. a: y set-plot-pen-color yellow
" K. k" x( j% e N$ ] q1 o2 \ plot count turtles with [color = yellow]& ?; m+ d* a% K4 A: x' r' L; I* ]
set-plot-pen-color green) e L# y0 l! j* p7 k' q& @
plot count turtles with [color = green]
& I$ U0 A9 N8 w: g* V0 {end
7 t+ S0 _% e$ }6 s7 p) c t8 cto update-lorenz-and-gini-plots
8 p) `0 l* k3 E set-current-plot "Lorenz Curve"; F( }; K$ ~" O+ ]% A( v: O& P/ _
clear-plot+ h1 X W5 A* w$ g
: Z% R7 C& q& F& h- ^- h
set-current-plot-pen "equal": O! O4 O h1 l0 p k( c
plot 00 `1 m7 N v8 p' b
plot 100
g( B( ?7 h1 c$ B) z
: k0 P" [: m0 A' n- G& [- o Q. {1 X set-current-plot-pen "lorenz"
! }/ W0 W% b: O2 ?+ ~7 k9 ?# u; ], k set-plot-pen-interval 100 / num-people
1 C0 Q$ m% ]( D* L0 h% K, Z* ~ plot 0/ x; X& h( b8 }. n
* P. g! E$ L; ~4 g7 z let sorted-wealths sort [wealth] of turtles
0 I7 e% S; D9 W( v t$ ^. q let total-wealth sum sorted-wealths
6 n: X" m9 e0 w$ v let wealth-sum-so-far 09 m7 s; t$ v5 |! E3 K6 v" V
let index 0* j4 v* Q3 W; y5 B# J7 N
let gini-index-reserve 0
}8 t2 u( [/ Q3 {8 W! J* L8 M) Q) G2 s
repeat num-people [
- l/ o& ?, n$ ]% [* b7 D set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
9 O5 Z' m: V& N- z plot (wealth-sum-so-far / total-wealth) * 100
4 j! h. ~* Q8 e$ w8 o0 U- t- p set index (index + 1)
& S ?: @8 ?3 @6 M set gini-index-reserve
! d5 g: _9 B: n+ L: u gini-index-reserve +, ]" L" x! b3 s) h: { Z
(index / num-people) -8 N, f! ~ R- g5 ]+ U
(wealth-sum-so-far / total-wealth)
- x0 @( K' i& m$ r4 R+ B2 } ]. v( y. }- W/ [8 U0 ]
$ p, n: @/ ]" }0 p" U
set-current-plot "Gini-Index v. Time"& Z# A( c5 a; d; Q! j' H
plot (gini-index-reserve / num-people) / area-of-equality-triangle
0 W4 m7 D; e( D- b! vend4 {3 [9 @. f5 _) M4 m+ g" h
to-report area-of-equality-triangle- z* l, V1 p* Q9 G/ | P0 I ]: S
report (num-people * (num-people - 1) / 2) / (num-people ^ 2)& k/ A% {3 o% ]2 V
end |