NDLI: Swarm/evolutionary intelligence for agent-based social simulation

Content Provider	IEEE Xplore Digital Library
Author	Janecek, A. Jordan, T. Buarque de Lima Neto, F.
Copyright Year	2014
Description	Author affiliation: Polytech. Sch. of Eng., Comput. Eng. Program, Univ. of Pernambuco, Recife, Brazil (Jordan, T.; Buarque de Lima Neto, F.) \|\| Res. Group Theor. & Applic. of Algorithms, Univ. of Vienna, Vienna, Austria (Janecek, A.)
Abstract	Several micro economic models allow to evaluate consumer's behavior using a utility function that is able to measure the success of an individual's decision. Such a decision may consist of a tuple of goods an individual would like to buy and hours of work necessary to pay for them. The utility of such a decision depends not only on purchase and consumption of goods, but also on fringe benefits such as leisure, which additionally increases the utility to the individual. Utility can be used then as a collective measure for the overall evaluation of societies. In this paper, we present and compare three different agent based social simulations in which the decision finding process of consumers is performed by three algorithms from swarm intelligence and evolutionary computation. Although all algorithms appear to be suitable for the underlying problem as they are based on historical information and also contain a stochastic part which allows for modeling the uncertainty and bounded rationality, they differ greatly in terms of incorporating historical information used for finding new alternative decisions. Newly created decisions that violate underlying budget constraints may either be mapped back to the feasible region, or may be allowed to leave the valid search space. However, in order to avoid biases that would disrupt the inner rationale of each meta heuristic, such invalid decisions are not remembered in the future. Experiments indicate that the choice of such bounding strategy varies according to the choice of the optimization algorithm. Moreover, it seems that each of the techniques could excel in identifying different types of individual behavior such as risk affine, cautious and balanced.
Starting Page	2925
Ending Page	2932
File Size	1287281
Page Count	8
File Format	PDF
e-ISBN	9781479914883
DOI	10.1109/CEC.2014.6900580
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Frequency selective surfaces Computational modeling Biological system modeling Remuneration Economics Decision making
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in