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Simulating the Emergence of Task Rotation 5 n* l# f8 J% w8 r5 K" u4 f- v
Journal of Artificial Societies and Social Simulation vol. 9, no. 1
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part06 共530字
: v7 G3 @# e% W请翻译，只有通顺正确的翻译才可能赢得悬赏！
3 g4 F( W; l5 ?7 y; W `work groups（工作组）, task rotation（工作轮换），multi agent simulation（多Agent仿真），emerge（涌现），task performance（任务绩效）。! s# L. E4 T2 K+ a) l2 P8 |$ V
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In all experiments, we used the following initial skill values of the agents (see Table 2). ' Z6 {; t( J3 i+ J& \' V
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| Table 2: Initial setting of the agents in all experiments2 B3 n4 `! U1 |% n+ h
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6 s+ o U' d, Y0 f5 v | Agent 1
* [* S) i" K* ~1 O @3 i) J | Agent 25 Y3 T. ]: u* k& B! O( X
| Agent 3
3 u2 o- C1 m( M7 u | Agent 4
* p; |) O# e b! s& o4 D2 X | Agent 5
6 R: j: ~. Y U5 z3 r | Skill 12 `* a, f/ T) ]6 I
| 11
6 A7 C }# O5 S1 X | 12( a5 ?5 E+ y' }% Z6 G! a+ K$ N
| 13
0 N0 V; [1 O* h | 14
6 S0 K2 Q( |1 X' H1 } | 15
* n: s& q+ Z2 ^& d; y/ P! S | Skill 2
+ D1 @: k* C" v( k, t# q | 12
! [( T3 q3 q ^ | 13) O0 [: o$ ^1 M( B4 z; d' H9 m
| 149 I( ?+ b: P0 T. h4 U6 }
| 15
+ b1 D' R5 G9 J1 S3 E4 P4 k7 ]4 R( L | 11
8 r& t/ I& a) S% D6 W9 L | Skill 3
, u% @' v- |+ U; ]% N3 W | 13& U7 X4 W& u s' H0 C
| 14
: b6 F" F+ R5 H( \* c | 15
+ q% p0 d8 Q; Z | 11
4 c( y q' p, p" e | 12
0 E! _" y4 F1 a# k8 m. w* A5 G | Skill 4, m2 M, S, }) F& _0 f4 F2 p
| 14
4 @( a. [+ P! \% Y: R | 15
7 T( h1 M* `& n& A | 11/ |. A: t0 n- P
| 12
0 _' e% B( w6 A1 F# E, E/ S a | 13
6 m5 n% y. u0 Y! q7 U" j | Skill 5$ u$ [" d% \, j8 L' l" @
| 15
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| 14
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We see that all the agents have the same pattern of values, but they are assigned to different skills. Initially, to each skill applied that the expertise value was the same as the motivation value. Therefore, in table 2, with each skill we mention only one value, representing both the initial expertise and the initial motivation. Although we start from these values, under the influence of expertise and motivational processes, the agents may decide to start rotating their tasks. - I. i! @ T/ w6 @$ c
8 J& a+ @+ G$ r T# W+ xTable 3. An example of task allocation
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Table 3 depicts an example of task allocation. The x-axis represents the cycles and the y-axis shows the skills. The numbers in the table refer to the agents using a particular skill. We see that the agents start in accordance with the initial values as described in table 2, i.e. agent 1 starts with skill 5, agent 2 starts with skill 4, etc. At the 12th cycle, the agents rotate for the first time, i.e. agent 1 rotates from skill 5 to skill 4, agent 2 rotates from skill 4 to skill 3, etc. This is represented by means of the coloured circles and the red arrows. During the next cycle, the agents rotate back, etc. This example depicts the actual task allocation as it occurs by using certain parameter values. Since we will give an elaborate description of expertise, motivation, and performance in the next section, in the actual allocation tables no information has been added. Therefore, we did not include them in the result section.
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In this section we have chosen not to depict all the results in detail, but to focus on the most interesting phenomena instead. Therefore, we will only present the results that show the most important aspects of the allocation processes and their outcomes. . B) I1 I/ T: \0 `& p% M, n# \
Organisation type 4.2 ( L S; U* z# y! p5 @; y+ ] n
In this section we will discuss the influence of the three organisation types, self-organisation, semi self-organisation, and no self-organisation, in a setting with a high degree of boredom/recovery. For the semi self-organisation type we used a rotation frequency of 1/5. We will discuss the expertise, motivation, and performance.
; M8 @0 |+ R, t5 qThe influence of self-organisation on expertise development 4.3
+ R4 l9 R& y, L4 M0 y& AIn accordance with the self-organisation type, the agents rotate between two skills (See Figure 4.1a). 3 s2 U# M" Z+ p
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Figure 4.1a. Expertise in case of self-organisation
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Figure 4.1a shows the development of expertise with respect to the five skills of agent 1. The x-axis represents the cycles and the y-axis shows the expertise. Since the agents are similar in the sense that they will all become specialised in the two skills with the highest initial value, and will forget the other three, we only show the results of agent 1. We see that the expertise in the second best skill of the agents increases after they have started rotating their tasks at the 12th cycle. The first time the agents rotate is determined by boredom. After that, they rotate after every cycle. As a result, the agents do not have time to forget their skills, but are able to increase their expertise. The semi self-organisation type shows about the same development of the expertise. No self-organisation leads to a situation in which the agents specialise in one particular skill while forgetting the other skills. |
发表于 2007-12-14 21:11:18
发表于 2007-12-14 21:11:19
