jasss系列："Simulating the Emergence of Task Rotation " P06

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+ O4 a8 s3 W- d+ fSimulating the Emergence of Task Rotation
/ S1 @3 W1 z' ~Journal of Artificial Societies and Social Simulation vol. 9, no. 1
) O' c, f2 [. U2 Z. b4 S# h8 Hhttp://jasss.soc.surrey.ac.uk/9/1/5.html;

( R) S1 S7 \8 `; Q3 hpart06 共530字
' {1 Q) d- n+ `6 I2 U- j' c请翻译，只有通顺正确的翻译才可能赢得悬赏！
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）。
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3.5
' h7 c& H8 ], J6 f+ t8 e9 E8 kIn all experiments, we used the following initial skill values of the agents (see Table 2).

Table 2: Initial setting of the agents in all experiments
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2 e3 T# W* ^7 X	Agent 1 7 @. m# Y" }$ ~! T6 ~. ?) A5 s	Agent 2	Agent 3	Agent 4 0 _2 \: i. O, Y	Agent 5 ! f1 e* K2 |+ ?5 v. Z, f. j3 \
Skill 1	11	12	13 6 q' o" r+ R* F$ q	14	15 5 F2 S9 P/ l7 b+ ~8 Z) @
Skill 2 5 `2 u; t2 U& }	12   S# X% |- \! E% u	13   w7 h! e  g$ T! I6 ]8 S" u& B	14	15	11 7 [3 q( a* \0 z: j1 b$ ~
Skill 3	13 & k" Z  _2 i( d	14	15 , C1 P- C6 X1 [# q: ]' Q+ [	11	12 0 n* W; B1 P5 p3 J* B0 b& @
Skill 4	14	15 % b8 L1 K" ^& V( _& Y9 j	11 # m' l9 i2 Y8 n	12	13
Skill 5 4 ?1 ]' R3 _- |2 p5 z# a	15 4 [4 m4 I0 T9 D	11	12 & ]5 {2 V- |# ]! C& x	13 ; b3 W# C6 @" \	14 3 g, P2 F! c2 E4 ?, v 8 u0 c$ r- T1 m7 b: h
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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.
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( W$ y9 Q7 J/ ]" w( T3 B! L' k3 FTable 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.
Results 4.1
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.
Organisation type 4.2
# [! B7 D' M4 @& K+ G; XIn 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.
& ^$ `9 W* F  ~3 O( OThe influence of self-organisation on expertise development 4.3
* g" R: ^( a5 Y6 ?! F+ V- FIn accordance with the self-organisation type, the agents rotate between two skills (See Figure 4.1a).
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( H! W, ^; c% f% D9 uFigure 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.

noone

3.5在全部实验过程中，我们使用以下Agent的基础资料（参阅表格2）。
* m+ r+ S- i; a: K) A% _表2：全部实验中Agent的初始设定
' {8 U" V+ A# I7 x9 D* z" P; p3.6 可以看到全部Agent有相同的数值模式，但是他们被分配予不同的技能。首先，对每项技能使用相同的专门技能数值与动机数值。 因此，在表格2中，每项技能我们只提及一个数值，用于描述那些初始专门技能和初始动机。虽然我们从这些数值开始，但是受专门技能和动机过程的影响，Agent可能会决定开始工作轮换。
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[ 本帖最后由 noone 于 2008-1-13 10:24 编辑 ]

noone

表3：一个工作分配的例子
" x0 A1 }  ~9 k& p( S3.7 表格3 描绘一个工作分配的例子。 x轴表示循环周期，y轴表示技能。表格中与Agent相关的数值使用了一项特殊的技能。我们可以看到Agent根据原始值开始，如表格2所描述。即Agent1以技能5开始，Agent2以技能4开始等。在第12个周期，Agent首次轮换，即Agent1从技能5轮换到技能4，Agent2从技能4轮换到技能3等等。这个转换由彩色的圆和红色的箭头来表示。在下一个循环期间，Agent向后轮换等等。这个例子描述了实际工作通过使用一定参数数值分配的情况。因为我们将会在下一节中对专门技能，动机和绩效进行详细的描述，在实际分配表中没有信息被加入。因此我们没有把它们列入结果中。

/ s0 y3 q& x3 t. b; [[ 本帖最后由 noone 于 2008-1-13 09:54 编辑 ]

noone

结论4.1
) f0 T) E- \, S3 \* g2 p在这一节，我们不会详细地说明全部结果，而是集中于最有趣的现象。 因此，我们将只给出显示分配流程和他们结果的最重要方面的结果。
组织类型 4.2
5 n/ N& X% M& O7 M0 \7 ^* p在这一节中我们将讨论在一个高度厌烦和恢复设定中存在的3 种组织类型，自组织，半自行组织，以及没有自行组织。 对于半自行组织类型我们使用1/5的轮换频率。 我们将讨论专门技能，动机和绩效。

+ G1 j, {2 m! T( H2 c" P) ~[ 本帖最后由 noone 于 2008-1-13 10:32 编辑 ]

noone

自组织对专门技能发展的影响
4 ?( S# r9 E$ }; o9 k' }4.3 根据自组织，Agents在两项技能之间轮换(参阅图4.1 A)。
- y% y" D; [$ L2 C$ i4.4 图4.1a 说明了关于Agent1 5种技能的专门技能发展。x轴表示周期，y轴表示专门技能。由于Agents在某种意义上是相似的，因此他们将全部专攻两项最高初始值的技能， 并且将忘记其他3种，我们只显示Agent1的结果。可以看到在第12个周期他们开始工作轮换之后，Agent的专门技能在第二种最佳技能中增加。第一次Agent轮换是由于厌烦。在那之后，他们在每个周期之后轮换。因此，Agents没有时间忘记他们的技能，但是能够增加他们的专门技能。半自行组织类型显示那些专门技能的发展几乎一样。没有自行组织导致Agents专攻于某种特殊技能的同时忘记其他技能。

[ 本帖最后由 noone 于 2008-1-13 10:33 编辑 ]