|
|
Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2016 Vol.17 No.4 P.283-295
Organizational dynamics in adaptive distributed search processes: effects on performance and the role of complexity
Abstract: In this paper, the effects of altering the organizational setting of distributed adaptive search processes in the course of search are investigated. We put particular emphasis on the complexity of interactions between partial search problems assigned to search agents. Employing an agent-based simulation based on the framework of NK landscapes we analyze different temporal change modes of the organizational set-up. The organizational properties under change include, for example, the coordination mechanisms among search agents. Results suggest that inducing organizational dynamics has the potential to increase the effectiveness of distributed adaptive search processes with respect to various performance measures like the final performance achieved at the end of the search, the chance to find the optimal solution of the search problem, or the average performance per period achieved during the search process. However, results also indicate that the mode of temporal change in conjunction with the complexity of the search problem considerably affects the order of magnitude of these beneficial effects. In particular, results suggest that organizational dynamics induces a shift towards more exploration, i.e., discovery of new areas in the fitness landscape, and less exploitation, i.e., stepwise improvement.
Key words: Agent-based simulation, Complexity, Coordination, Distributed search, NK landscapes
Chinese Summary <29> 自适应分布式搜索过程中的组织变化及问题复杂度对性能的影响
创新点：基于分布式多智能体的仿真分析了组织设置的不同模式变化对于不同复杂度的搜索问题的影响。
方法：首先介绍了所采用的智能体仿真模型，描述了构建在NK适应度曲面上的分布式搜索问题及其复杂度。接着阐述了组织设置包括搜索智能体和核心智能体的设置、搜索智能体的视角形成、不同搜索智能体之间的协调以及搜索多样性等。然后给出组织动态性的数学描述，并进行了实验分析：（1）比较了组织变化对子问题交互复杂度最大和最小两种极端搜索问题的影响（称之为“基准”）；（2）分析最终和平均优化性能对搜索问题复杂度的敏感性；（3）分析交叉智能体交互复杂度对性能影响的不稳定性。
结论：本文的研究表明组织动态变化能够增加分布式自适应搜索的有效性，比如提高最终性能表现、增加获取最优解的可能性以及发现新的解域等。这种有效性增加幅度很大程度上取决于组织变化模式以及问题的复杂度。
关键词组：
References:
[1]Altenberg, L., 1997. NK fitness landscapes. In: Back, T., Fogel, D.B., Michalewicz, Z. (Eds.), Handbook of Evolutionary Computation. Oxford University Press, UK, p.B2.7:5-B2.7:10.
[2]Baumann, O., 2013. Distributed problem solving in modular systems: the benefit of temporary coordination neglect. Syst. Res. Behav. Sci., 32(1):124-136.
[3]Cao, Y., Yu, W., Ren, W., et al., 2013. An overview of recent progress in the study of distributed multi-agent coordination. IEEE Trans. Ind. Inform., 9(1):427-438.
[4]Carley, K.M., Gasser, L., 1999. Computational organization theory. In: Weiss, G. (Ed.), Multiagent Systems: a Modern Approach to Distributed Artificial Intelligence. MIT Press, Cambridge, p.299-330.
[5]Gross, T., Blasius, B., 2008. Adaptive coevolutionary networks: a review. J. Royal Soc. Interf., 5(20):259-271.
[6]Hansen, M.T., 1999. The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits. Administr. Sci. Quart., 44(1):82-111.
[7]Karp, R.M., Upfal, E., Wigderson, A., 1988. The complexity of parallel search. J. Comput. Syst. Sci., 36(2):225-253.
[8]Kauffman, S., 1993. The Origins of Order: Self-Organization and Selection in Evolution. Oxford University Press, UK.
[9]Kauffman, S., Levin, S., 1987. Towards a general theory of adaptive walks on rugged landscapes. J. Theor. Biol., 128(1):11-45.
[10]Law, A., 2007. Simulation Modeling and Analysis. McGraw-Hill, USA.
[11]Levitan, B., Kauffman, S., 1995. Adaptive walks with noisy fitness measurements. Mol. Divers., 1(1):53-68.
[12]Li, R., Emmerich, M.T.M., Eggermont, J., et al., 2006. Mixed-integer NK landscapes. Proc. 9th Int. Conf. on Parallel Problem Solving from Nature, p.42-51.
[13]Peterson, C., 1990. Parallel distributed approaches to combinatorial optimization: benchmark studies on traveling salesman problem. Neur. Comput., 2(3):261-269.
[14]Rivkin, J.W., Siggelkow, N., 2007. Patterned interactions in complex systems: implications for exploration. Manag. Sci., 53(7):1068-1085.
[15]Siggelkow, N., Levinthal, D.A., 2003. Temporarily divide to conquer: centralized, decentralized, and reintegrated organizational approaches to exploration and adaptation. Organ. Sci., 14(6):650-669.
[16]Siggelkow, N., Rivkin, J.W., 2005. Speed and search: designing organizations for turbulence and complexity. Organ. Sci., 16(2):101-122.
[17]Thompson, J.D., 1967. Organizations in Action: Social Science Bases of Administrative Theory. McGraw-Hill, USA.
[18]Wall, F., 2010. The (beneficial) role of informational imperfections in enhancing organisational performance. Progress in Artificial Economics, p.115-126.
[19]Wall, F., 2013. Comparing basic design options for management accounting systems with an agent-based simulation. Proc. 10th Int. Conf. on Distributed Computing and Artificial Intelligence, p.409-418.
[20]Wall, F., 2015. Effects of organizational dynamics in adaptive distributed search processes. Proc. 12th Int. Conf. on Distributed Computing and Artificial Intelligence, p.121-128.
[21]Wall, F., 2016a. Agent-based modeling in managerial science: an illustrative survey and study. Rev. Manag. Sci., 10(1):135-193.
[22]Wall, F., 2016b. Beneficial effects of randomized organizational change on performance. Adv. Complex Syst., 18(5-6):1550019.1-1550019.23.
[23]Welch, B.L., 1938. The significance of the difference between two means when the population variances are unequal. Biometrika, 29(3/4):350-362.
Open peer comments: Debate/Discuss/Question/Opinion
<1>
DOI:
10.1631/FITEE.1500306
CLC number:
TP13
Download Full Text:
Downloaded:
2274
Download summary:
<Click Here>Downloaded:
1749Clicked:
7684
Cited:
3
On-line Access:
2016-04-05
Received:
2015-09-21
Revision Accepted:
2016-01-05
Crosschecked:
2016-03-09
Tel: +86-571-87952276; Fax: +86-571-87952331; E-mail: jzus@zju.edu.cn
Copyright © 2000~ Journal of Zhejiang University-SCIENCE