Modeling of Theme Park Problem with Multiagent for Mass User Support

Kawamura, Hidenori; Kurumatani, Koichi; Ohuchi, Azuma

doi:10.1007/978-3-540-24666-4_4

Cited by 25 publications

(15 citation statements)

References 6 publications

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“…Our previous study shows it is difficult to optimize individual behavior in the complicated theme park model because optimal behavior is easily changed by the theme park setting (11) . In a real environment, the users may not be able to understand how to recognize the environment and how to measure the effectiveness of choices in their real lives, and they may not be able to achieve user equilibrium, much less system equilibrium.…”

Section: Discussionmentioning

confidence: 99%

“…The theme park problem is one example of mass user support research (11) , that consists of two kinds of elements, a spatial component and a software agent. The spatial component of the theme park may be one of several types; attraction, road, plaza, entrance, and exit.…”

Section: Theme Park Problemmentioning

confidence: 99%

“…Therefore, we focus on the theme park problem (11) , a multiagent model for studying individual visiting activity and global performance, and clarify the relationship between global performance and congestion avoiding behavior. In the theme park problem of this paper, there are two attractions providing services.…”

Section: Introductionmentioning

confidence: 99%

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Investigation of Global Performance Affected by Congestion Avoiding Behavior in Theme Park Problem

et al. 2004

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We focus on the simple theme park problem, where there are two attractions and visitor agents which select their destination attraction based on congestion disregarding behavior and congestion avoiding behavior. According to the computer simulation, the result shows that the growth of individual congestion avoiding behavior is not always effective for improving global performance, and this phenomenon is caused by the oscillation of successive selection switching of the same destination by many congestion avoiding agents. Although the model and setting of this paper is simpler than other related works, we consider each phenomenon in those works has the same characteristic based on the ineffectiveness caused by the homogeneity of congestion avoiding behavior and information sharing.

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Section: Discussionmentioning

confidence: 99%

Section: Theme Park Problemmentioning

confidence: 99%

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Investigation of Global Performance Affected by Congestion Avoiding Behavior in Theme Park Problem

et al. 2004

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“…Some researchers are interested in personal tourism navigation systems, which navigate users by displaying routes to given destinations [1], [2]. Furthermore, some researchers are interested in congestion-aware scheduling methods for multidestination travels [3], [4], [7]- [9]. Those navigation systems focus mainly on guidance for personal use.…”

Section: Related Workmentioning

confidence: 99%

The Adaptive Recommendation Mechanism for Distributed Group in Mobile Environments

Cheng

Horng

Chou

2012

IEEE Trans. Syst., Man, Cybern. C

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Tourism navigation systems have become an important research area because they help people strengthen their focus on the quality of the tourism. This paper proposes an adaptive recommendation mechanism that rests on a congestion-aware scheduling method for multigroup travelers on multidestination travels. This recommendation scheme uses the pheromone mechanism of an ant algorithm for group system distribution. In order to reduce congestion in the "visiting multiple destinations" problem that might beset the multiple groups, we present a tour group that could take adaptive recommendations from a system that would yield a high quality tour experience, wherein the group would visit a secondary destination first and then visit the primary destination. Simulation results reveal the strengths of the proposed "adaptive recommendation mechanism" model in terms of decreasing average waiting time, congestion, and the ratio of congestion avoiding to number of groups.

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“…Kurumatani puts forward a social coordination mechanism for mass user support [3]. The social coordination mechanism for mass user support is tested by the Theme Park Problem [4]. A simple route guiding mechanism for mass user support is proposed to reduce traffic congestion and driver get access to the shortest route in time using route information sharing [5].…”

Section: Introductionmentioning

confidence: 99%

Multi-stage Dynamic Coordination Model for Large-Scale Crowd's Activities Based on Multi-agent

Dao-li

et al. 2009

2009 WRI World Congress on Computer Science and Information Engineering

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In order to reduce the phenomena of long time queuing and congestion in large-scale crowds' activities, improve the visitors' satisfaction and increase social welfare, a multi-stage dynamic coordination model for large scale crowds' activities based on multi-agent is proposed and a coordination algorithm PCI is designed. Three types of basic coordination algorithms are tested by computer simulation, and the simulation results are used to discuss the basic characteristics of the problem. The results indicate that coordination algorithm PCI can reduce the congestion significantly and ensure better social welfare while meeting the real-time requirement.

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Modeling of Theme Park Problem with Multiagent for Mass User Support

Cited by 25 publications

References 6 publications

Investigation of Global Performance Affected by Congestion Avoiding Behavior in Theme Park Problem

Investigation of Global Performance Affected by Congestion Avoiding Behavior in Theme Park Problem

The Adaptive Recommendation Mechanism for Distributed Group in Mobile Environments

Multi-stage Dynamic Coordination Model for Large-Scale Crowd's Activities Based on Multi-agent

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