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! ~& k) ]6 y$ w# m
globals# [; t+ g7 `; x
[
" g, e. U/ v9 ~' E3 Y$ {& P f7 A max-grain / l7 v1 y, f& `- E" h# z) ~. ^
' j+ i: z+ L- k
]6 `) p$ u- s1 Q$ P- U+ H/ G( A
! R& }9 `% u0 T: U0 v2 S' }patches-own3 x; w# C/ @2 i& J7 u7 S
[; W1 f9 N6 S; H/ d$ I* k( i
grain-here
( H0 ^/ x4 F# h- q max-grain-here + ^8 C; r R+ U3 r. y. P( N+ d- ~9 l
]. h! D; H c7 o. a6 F
; e5 }3 C+ z* Y6 q1 Vturtles-own5 u+ U3 B+ G+ F6 E
[! x8 q+ V: l! V D
age
' I9 `5 u' ]- B' w8 f* t# I# f- P; o wealth
/ |: y0 Q+ ~4 b7 m life-expectancy ! Y# N; h- Z- r7 L. L6 A
metabolism
5 T) ~3 R6 N, s: y' T1 U0 V! \+ L vision
* G9 [8 Q4 i3 v2 B+ h J inherited
* o4 I4 c( e: w" V]# {" K! ?/ Q% l5 q$ L
9 E0 o& y. c/ f' q% B
. l( y7 k ?. V9 X H
to setup
, \% |% v8 f% c) m* n0 o$ ? ca8 l0 X. T* l8 a- c! q
set max-grain 50
4 H$ Q2 q' d( I# F2 y0 u setup-patches
' i/ H X/ K* L! V) X/ p setup-turtles. D) W2 H0 d1 j/ J2 d
setup-plots( g! h( C9 `7 W6 l# C
update-plots9 k3 D b1 N1 o+ i; Y
end8 \* ]8 F# l3 Q0 [7 w# J) P
to setup-patches5 Y E4 F5 {# B; n* B
ask patches
# `! _& m! y v [ set max-grain-here 0& I' }& H1 X! g, W/ U
if (random-float 100.0) <= percent-best-land
0 {0 V4 f4 y: Q- _- ^3 e' R R [ set max-grain-here max-grain
, x2 Q& Z# J2 ?4 C1 `8 @) M) z6 y set grain-here max-grain-here ] ]
0 \' o& f& c4 _: `" w: _ repeat 5
; l' N% ?% K; U# {" i [ ask patches with [max-grain-here != 0]5 E$ `" f! \1 ^, m% \5 A/ \
[ set grain-here max-grain-here ]; O2 W5 K7 G8 r- F' s; H
diffuse grain-here 0.5 ]
; |3 h* G* u, A+ ?% u repeat 10
- S( t- s/ g4 Z" ^ [ diffuse grain-here 0.5]
F9 M4 j4 H: ~7 \, l ask patches, L+ [; D# ~/ v6 E" ~' o
[ set grain-here floor grain-here . k2 s7 ?2 ]" R* p9 W! e
set max-grain-here grain-here
! g, i' ^8 l& O) w recolor-patch ]
" a' b0 U2 C% p, R' F# @0 }$ Jend+ W q/ t. A/ I5 |6 s' D3 o
to recolor-patch 0 {6 _3 S8 r# S' G. I: l1 n
set pcolor scale-color sky grain-here 0 max-grain6 `# H2 K5 h4 p7 \5 |5 w
end* p2 a+ Z4 p% @2 c
to setup-turtles8 h# j8 q4 c& y
set-default-shape turtles "person", z, j" ^* \6 K/ D3 V0 A
crt num-people3 @# R% D: H. Y& o' J! z. @- a
[ move-to one-of patches ! Q, B1 B7 h4 f/ R
set size 1.5 : s- Q" v2 _9 D
set-initial-turtle-vars-age6 Y0 ? @) B: d* C
set-initial-turtle-vars-wealth% R5 ~1 q5 m4 N8 L+ m+ O" k6 Z. k
set age random life-expectancy ]
% n1 R$ ^& S% O; f/ Z% G recolor-turtles- n, K3 O* Q* u" o1 q+ Y
end, a$ ~: ~$ h2 g1 Y
& @2 i3 {+ v4 l) z0 w+ Cto set-initial-turtle-vars-age
5 D3 @% C' V5 W8 S2 s3 x! _ let max-wealth max [wealth] of turtles
7 X: w' H" f, K7 w: W 5 A0 _2 U; K1 h$ J4 h$ v5 ?
ifelse (wealth <= max-wealth / 3)
+ t' c$ Y2 L9 [& \) F/ G% w [ set color red
" u! l! J2 G# G8 G2 r% X set age 0! \! Z% U1 g* H2 s" Y3 I+ o y
face one-of neighbors4 + s' l. K( G, ?; T
set life-expectancy life-expectancy-min +
. S; `! L6 B) a: c random life-expectancy-max $ M6 I, a) x0 _& b! N+ N4 b6 j& d
set metabolism random 1 + metabolism-low+ R9 g: \! a- x, ~- H$ w7 u
set wealth metabolism + random 30
6 Q& ]/ k; y. q2 q& V. O5 y set vision 1 + random max-vision
6 o4 R4 H# I0 X m( u3 \, P- ~ set wealth wealth + Wealth-inherited-low ]: T7 x% h+ }9 d1 @$ ~: d& D: f$ D
[ ifelse (wealth <= (max-wealth * 2 / 3))) `. q- F: |, E5 x
[ set color yellow ; e E2 \2 S+ V9 W1 C2 N
set age 0; f1 o! k. A, m3 W, y5 c3 ^
face one-of neighbors4
) a' t/ P7 a0 n2 V" y set life-expectancy life-expectancy-min +
* Q7 x8 V) P, E* F' ~# y random life-expectancy-max + 1' {& L! e* C/ O/ z
set metabolism 1 + random metabolism-mid. d& D4 v8 T" ~# J, t. J% s, R% V
set wealth metabolism + random 301 ^) o6 X; `" D/ a% ~1 x
set vision 3 + random max-vision
2 `. T, `( U1 a( a* O H set wealth wealth + Wealth-inherited-mid]
) @! l; n! ^9 E/ l [ set color green
# X F& i2 E" n$ @ set age 09 Z: x$ g `. _: e. k
face one-of neighbors4
+ }5 L6 J/ P" K& K set life-expectancy life-expectancy-min +
( T O/ J7 x8 A; F random life-expectancy-max + 2
; b i7 ~) u0 K- ^9 p, u- B0 K set metabolism 2 + random metabolism-up' C; r9 F1 |7 k$ R3 v6 u
set wealth metabolism + random 30
+ ^9 R; p8 l) E set vision 3 + random max-vision, | l* c% N8 t) x$ o
set wealth wealth + Wealth-inherited-up ] ] 6 {& u7 j: N8 e7 @5 k
5 a2 u, H+ Y$ ^" Q6 Y. Xend
' H( \! ^& ]* b; t0 v5 J2 n) sto set-initial-turtle-vars-wealth2 u: D0 j% J$ g! m) i) g- e* M' a* i
let max-wealth max [wealth] of turtles7 p. u8 J' u) Q( I$ ~2 l0 c
set age 0
2 k" T @% g) F; y% z. u* X1 U* M- { face one-of neighbors4
5 ^3 k' e- T, o4 w' R set life-expectancy life-expectancy-min +, ] _: `, }. w7 W& V, I
random life-expectancy-max 3 U2 ^3 d; N" _2 j3 m5 y& e8 {
set metabolism 1 + random metabolism-up+ h$ F% B) J4 X" E8 v- {# t
set wealth metabolism + random 309 X3 @8 E+ C7 x
set vision 1 + random max-vision
. P6 s6 E4 p9 Rend
1 {* }3 u+ c% ?3 v P7 c) }: U4 l: K" @to redistribution! W2 I. Q+ U# b
let max-wealth max [wealth] of turtles
7 F. y# r. X5 O6 @ T A. \let min-wealth min [wealth] of turtles+ W; Z) ~ ^9 K. d+ u5 z
if (wealth <= max-wealth / 3)
# z( j, W, c: H; `/ P( f0 z [set wealth wealth + Low-income-protection ]5 S0 Y; m; h7 E7 Y! ^7 P
end
' V" y8 @! t' ~
7 g) ~; \: H# X% B! bto recolor-turtles
0 E) Q* B* Q7 Y. I2 ], W let max-wealth max [wealth] of turtles
3 k3 W0 Z3 t9 z* `$ w! W ask turtles
3 t2 S8 X0 i+ ~ [ ifelse (wealth <= max-wealth / 3)
6 |& V! J/ } q. ?# @. S$ V4 q [ set color red ]
4 G) r6 o% C$ C6 { [ ifelse (wealth <= (max-wealth * 2 / 3))
% |) N9 g8 a2 [1 T2 h [ set color yellow ]3 j( M- B$ V+ D+ @; h+ h8 k, Q3 @
[ set color green ] ] ]
" ^8 |# r) C! D; K4 F ask turtles [ifelse show-wealth?
$ l3 i- @, K4 ]% E0 s [ set label wealth ]* G' Y) q( I/ ?8 [' _
[ set label "" ]]
5 ?. y" ]1 w1 cend
* L/ q$ R4 D% j9 ^% y0 F. R- H2 i' O# D9 J- z
to go
% P, s6 Z: C/ D* U7 P ask turtles7 `4 ^3 j3 e: U' D
[ turn-towards-grain ] 2 G, h s7 C- s& L' l
harvest- f1 b, c. _& q/ _* [2 }
ask turtles
0 @$ |' O# y7 p3 B p [ move-eat-age-die ]5 v7 z4 D7 p7 k
recolor-turtles
2 `8 o5 n5 c& f) b2 E( E7 t9 C if ticks mod grain-growth-interval = 0
1 G4 E+ J7 }+ R! C/ M& n9 c [ ask patches [ grow-grain ] ]
% Q, U' w& v: w0 S: A) {5 l6 @
' k2 Z- Z; U7 k2 G! r" w if ticks mod 11 = 0
. J$ l5 F% `/ L5 i1 u* s; W [ask turtles
Z* B( O6 ^0 |' b [. z [ redistribution ]]
" ]1 X$ r; x& x, F5 B8 H if ticks mod 5 = 0: G, l; o! f0 w1 h, U( [
[ask turtles
9 B. `* h, L% P; T* `; m [ visions ]]9 R0 v N; `( h( X+ ?1 ]- ]; }$ A
tick
. u" h& v" K' ~ z; o" v update-plots% [) }& U2 S$ H! L% M" n/ J0 Q
end
5 D+ U1 u+ Q4 D$ Z2 }( c4 [to visions: Q1 f/ k6 @/ P# F
set vision vision + 1
9 {6 d; R- Z9 J0 B& O6 b2 h+ rend
) i S) y- \% l" S) _* N! q
6 _; M5 n4 m% Y! u+ f+ ^/ ]% _! e3 l9 M; F$ w
+ M! D& s6 V& w: ]1 w( F
to turn-towards-grain 7 n6 J6 D5 D& Y7 i" j
set heading 03 g0 z* M) F/ J& U3 s) G
let best-direction 0* @$ D. y# A% `" X# y
let best-amount grain-ahead2 Q2 W8 c# Q) O, D/ z! D
set heading 90
& \& d/ y% @) Z z0 z7 c$ S if (grain-ahead > best-amount)( r6 ` z# N" \% u9 f b" h$ ?
[ set best-direction 90
8 e5 F" N3 l7 }% L* _: ? set best-amount grain-ahead ]
! c. w" j) T$ {5 T) u set heading 1809 C, m6 r9 i/ a* Y3 f1 s
if (grain-ahead > best-amount)! V7 n% x/ W4 {; z$ m- A( ]* ~% f0 \
[ set best-direction 1802 x$ p% U4 o+ O6 {+ r m
set best-amount grain-ahead ]6 G& W+ |$ Y% b8 a0 G, I5 K. V4 _2 u V
set heading 270
) [1 W# Q) N+ S7 u! I if (grain-ahead > best-amount). I& ^$ p- U& T- L* L9 @$ j7 Q
[ set best-direction 270
2 y2 I' l4 _+ e8 _3 |+ k8 T/ m set best-amount grain-ahead ]
* q% _! v2 x$ Q( Y4 b! X5 C2 K7 D) Y set heading best-direction0 v# m& ]5 B4 I
end
/ O7 G9 h/ o3 |0 S; ]
1 U+ w7 h2 m, E1 ~& D( w8 ]. m' W# u" }8 w k7 M
to-report grain-ahead 6 k- C0 M% E8 w. j+ D9 D/ z
let total 0, m: u5 B2 W6 A0 a7 T, }
let how-far 1
8 ]$ c! O R1 _& O P repeat vision
. F# b: [5 f* ]: }* i. [. o8 E [ set total total + [grain-here] of patch-ahead how-far
8 V$ Z8 Y1 R3 N6 `# d$ V set how-far how-far + 1 ]8 [' A& x* x" y& C
report total: n! Q* I6 P" L+ X' G' q
end
2 P4 m7 g6 C+ ~) m2 @5 Z+ T
1 z+ l1 q% c% Q9 p( v8 ]to grow-grain
; x4 H- s+ N$ r+ |4 { O if (grain-here < max-grain-here)
& H, s6 v* `$ h' g [ set grain-here grain-here + num-grain-grown
: L. G+ x2 g; y: `7 l if (grain-here > max-grain-here)
& ?4 v" N; N( A9 v [ set grain-here max-grain-here ]3 S" C, ~' p4 }
recolor-patch ]" H0 }3 T9 b1 J" }. Q" \5 [* Y
end
7 A E; R4 c/ D& c$ Z+ u4 s6 tto harvest- T0 T" B% U9 H% F1 g
ask turtles: l5 U& S9 C0 P. ^. N* h
[ set wealth floor (wealth + (grain-here / (count turtles-here))) ]8 L3 u$ J/ G! B9 p' u8 J, X$ w
ask turtles% @' q; c, x( Q# Y! K' t
[ set grain-here 0
4 Q |, H6 h* e4 W recolor-patch ], B6 K- u, D' H- a( L
d# X% [+ q6 J+ kend
5 I1 G7 m1 G6 ^3 K. O1 x- V$ \: Q! _. U. `: T- C
to move-eat-age-die % r9 [! S% W1 T
fd 1) K) _. h d1 t+ b8 D, b) u; I; C$ o
set wealth (wealth - metabolism)
% G9 ^1 M1 k7 q+ \# I' B set age (age + 1)# r* `7 `$ o6 f; Z$ e& j
if (age >= life-expectancy)& T8 F9 K- |# e7 H5 ]
[ set-initial-turtle-vars-age ]
7 n5 o% N: i% N1 f6 Y if (wealth < 0)
7 e$ @2 I6 ~) b [ set-initial-turtle-vars-wealth ]
* T. l/ Z; S& d/ M9 K( g. Y- F $ ^% z8 u( m8 F. }
end
. M, @) H$ ]1 h! e6 f2 m% R% `
2 F8 Q: m/ k+ E& G; {! _ Q( m7 _- O7 x! ~2 B
to setup-plots
: J) a) h& h; D+ \. |* X% E" z set-current-plot "Class Plot") M- W1 t0 P7 ^0 i# D2 L, x" G; z
set-plot-y-range 0 num-people
. d( p# h) o4 y+ w: @0 O% S# }0 @ set-current-plot "Class Histogram". F$ \: T. w# `* ^) p. C
set-plot-y-range 0 num-people2 {6 f2 f3 g/ u+ c' V
end0 v( Y+ q, F0 h* a7 h) s
7 v' _+ f# p) U# \/ Y& Hto update-plots2 C' B+ j7 c0 m, R
update-class-plot) A" t1 [' T5 k4 U i: L
update-class-histogram
6 g# a% o5 P% e( j @ update-lorenz-and-gini-plots
! s* o% R% |7 A! G9 x: b1 I& ]* Lend( |. w4 o% b5 ?- R0 n8 ]' q
. N* z' @, ]; S% L0 v H7 h
to update-class-plot9 K( @6 Y C Z3 I$ V: x" }3 L1 o
set-current-plot "Class Plot"
7 f* t$ a \: C5 Y set-current-plot-pen "low"( G1 f2 g% r: A5 C+ `9 n
plot count turtles with [color = red]* N3 y( Y) h5 F* E8 L9 T! }& C1 a
set-current-plot-pen "mid"
0 {- G& a4 g0 O" J plot count turtles with [color = yellow]
! A) w4 j4 A& ]8 O8 Y set-current-plot-pen "up"4 J: P. Y+ i" u- e
plot count turtles with [color = green]
U+ @" M3 z$ T1 X. `end
( f9 t* I1 [! a# r* G& |2 F, G) q
to update-class-histogram
- r/ ?+ y9 c8 O5 z" R set-current-plot "Class Histogram"
, }- |: {& Z; ?; B$ C6 H plot-pen-reset
9 j* X/ [' c+ c! h set-plot-pen-color red
1 z4 f9 e' ?* J0 S1 ] plot count turtles with [color = red]" v: P( @; h3 p% C8 H# `
set-plot-pen-color yellow8 G ~! ?) L$ n: z
plot count turtles with [color = yellow], d: B" n3 Y. p# m2 c4 f2 I
set-plot-pen-color green
% }. }0 ^1 E4 t plot count turtles with [color = green]
! ]7 [6 T9 j3 q5 |4 j2 Oend
" J; ~: z& ?; }, g; o: [1 o* nto update-lorenz-and-gini-plots
( x/ a+ ]5 O& H set-current-plot "Lorenz Curve"
& J0 F/ ]% j1 J clear-plot
/ q. k3 u# u2 t* Q d% M$ ^* S6 x
; V$ \, x O9 f: S9 T. K set-current-plot-pen "equal"
" y4 H) H& r# W3 `: d; p* e plot 0
/ q! Z- h: Q R plot 100
* Q( S* f, P; u+ {8 i% u6 @4 }
- `. s$ r. K8 e f: j1 w2 N set-current-plot-pen "lorenz"8 s/ n( l- }3 \) w
set-plot-pen-interval 100 / num-people
5 S& F# g- V7 {/ F1 D plot 0$ a2 t+ d% P1 ]3 \ G
* e$ G \7 P1 W4 h; x
let sorted-wealths sort [wealth] of turtles
$ O; u9 z h+ r/ V let total-wealth sum sorted-wealths6 O& U) {7 \+ Z2 ~
let wealth-sum-so-far 0
! L! y8 V9 m0 k" h2 H5 h, k) r3 c let index 0( B* m% @8 E7 A, s! m0 c8 i
let gini-index-reserve 02 t' p5 E1 L$ d8 \! p1 ~) w
. L7 G) j* V4 {) m' G; `
repeat num-people [5 x- q0 h) N( P
set wealth-sum-so-far (wealth-sum-so-far + item index sorted-wealths)
8 g! `% a" `) G5 V4 l) _" e: A plot (wealth-sum-so-far / total-wealth) * 100- Q/ D' o4 M( z* Y
set index (index + 1), \9 k, {, p" w. I! W
set gini-index-reserve
8 R c. ~% w+ O n. h- Z gini-index-reserve +4 E1 ^$ l# j- g. O& _
(index / num-people) -, R2 L2 Y4 U/ `% T) s* l1 Z/ Y
(wealth-sum-so-far / total-wealth)
3 F8 k; z' |2 v/ W1 o7 [/ D ]
F" ^ I; }5 w2 ]' b
- _! o" i5 j8 |) L [7 @! O+ P1 {7 j7 | set-current-plot "Gini-Index v. Time"
3 R& B: e# F9 H. z plot (gini-index-reserve / num-people) / area-of-equality-triangle
' h, A6 E7 k9 s) ~5 n* `end% W3 Z& J# W, `' y& ]
to-report area-of-equality-triangle
1 `, O0 ?7 r, b4 u1 T8 W& P report (num-people * (num-people - 1) / 2) / (num-people ^ 2)) k1 n W9 Q- Y- L1 ^2 [
end |