A general computational recognition primed decision model with multi-agent rescue simulation benchmark

2012 ◽  
Vol 187 ◽  
pp. 52-71 ◽  
Author(s):  
Alireza Nowroozi ◽  
Mohammad E. Shiri ◽  
Angeh Aslanian ◽  
Caro Lucas
Keyword(s):  
Decision Model ◽  
Multi Agent

scholarly journals Dynamic Route Decision Model-based Multi-agent Evacuation Simulation - Case Study of Nagata Ward, Kobe

2008 ◽  
Vol 28 (2) ◽  
pp. 91-98 ◽  
Author(s):  
Yuling Liu ◽  
Norio Okada ◽  
Yukiko Takeuchi
Keyword(s):  
Decision Model ◽  
Evacuation Simulation ◽  
Model Based ◽  
Multi Agent ◽  
Dynamic Route

scholarly journals Discrete decision model and multi-agent simulation of the Liang Zong two-chain hierarchical organization in a complex project

2018 ◽  
Vol 29 (2) ◽  
pp. 311-320
Author(s):  
Qiang MAI ◽  
◽  
Yueqiang ZHAO ◽  
Shi AN ◽  
Keyword(s):  
Decision Model ◽  
Hierarchical Organization ◽  
Agent Simulation ◽  
Multi Agent ◽  
Complex Project

scholarly journals Simulation and Analysis of Urban Production–Living–Ecological Space Evolution Based on a Macro–Micro Joint Decision Model

2021 ◽  
Vol 18 (18) ◽  
pp. 9832
Author(s):  
Yuanyuan Tao ◽  
Qianxin Wang ◽  
Yan Zou
Keyword(s):  
Urban Space ◽  
Decision Model ◽  
Local Environment ◽  
Joint Decision ◽  
Space Planning ◽  
Evolution Simulation ◽  
Living Space ◽  
Ca Model ◽  
Multi Agent ◽  
Precise Simulation

The precise simulation of urban space evolution and grasping of the leading factors are the most important basis for urban space planning. However, the simulation ability of current models is lacking when it comes to complicated/unpredictable urban space changes, resulting in flawed government decision-making and wasting of urban resources. In this study, a macro–micro joint decision model was proposed to improve the ability of urban space evolution simulation. The simulation objects were unified into production, living and ecological space to realize “multiple planning in one”. For validation of the proposed model and method, remote sensing images, geographic information and socio-economic data of Xuzhou, China from 2000 to 2020 were collected and tested. The results showed that the simulation precision of the cellular automata (CA) model was about 87% (Kappa coefficient), which improved to 89% if using a CA and multi-agent system (MAS) joint model. The simulation precision could be better than 92% using the prosed model. The result of factor weight determination indicated that the micro factors affected the evolution of production and living space more than the macro factors, while the macro factors had more influence on the evolution of ecological space than the micro factors. Therefore, active policies should be formulated to strengthen the ideological guidance towards micro individuals (e.g., a resident, farmer, or entrepreneur), and avoid disordered development of living and production space. In addition, ecological space planning should closely link with the local environment and natural conditions, to improve urban ecological carrying capacity and realize urban sustainable development.

AI and intelligent buildings: Multi agent comfort and energy systems for building management systems

2012 ◽  
Author(s):  
Wim Zeiler ◽  
Rinus van Houten ◽  
Gert Boxem ◽  
Joep van der Velden
Keyword(s):  
Energy Systems ◽  
Management Systems ◽  
Intelligent Buildings ◽  
Building Management ◽  
Multi Agent ◽  
Building Management Systems

A Fixed Observation Boundary Decision Model for Detection of Change

1974 ◽  
Author(s):  
Graham J. Burkheimer ◽  
William E. Stein ◽  
Amnon Rapoport
Keyword(s):  
Decision Model
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