Spatial agent-based modeling of household and firm location with endogenous transport costs

Tsekeris, Theodore; Vogiatzoglou, Klimis

doi:10.1007/s11066-011-9060-y

Cited by 13 publications

(13 citation statements)

References 39 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…В модели используются схемы «одобрения Коэнов» для моделирования когнитивного обучения фирм. Эта методология основана на теории когнитивной науки и позволяет моделировать обучение путем исследования, использования и имитации знаний [30].…”

Section: модель инновационного развития отраслейunclassified

Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential

Abramov

Кудинов

Evdokimov

2019

Vestn. Voronež. gos. univ. inž. tehnol.

View full text Add to dashboard Cite

Agent based models (ABM) and multiagent systems (MAS) can be used to solve problems in many fields of research - from natural and computer to economics and social sciences. Many natural and social phenomena can be represented in form of complex simulations so over time agent models and multi-agent systems have proven to be a really powerful tool in areas such as economics and trade, health, urban planning and social sciences. In addition multi-agent systems can be represented as an artificial society similar to a human one and consisting of entities with characteristics similar to human ones, for example in terms of autonomy and intelligence. ABM are based on the principle of objective orientation as well as the evolution (training) of agents in the process of modeling various variants of the proposed events. Despite the apparent simplicity of the rules of interaction between agents the results are usually non-obvious and quite meaningful. ABM can be developed both at the micro level and represent models with multiple agents at the macro level. The concept of multi-agent systems which immediately gained followers and support in both scientific circles and industrial communities, first started talking in the mid-1980s. Over the past thirty years, the methodology of IAU creation has been constantly improved: technologies and tools for its promotion and use in the management of large-scale network structures (such as defense systems, energy, health, transport, logistics, urban management, collective robotics, etc.) have been actively developed. The scope of application of MAS is very wide. The analysis of implemented MAS proves that currently the tool is the most advanced technology for managing any objects built on the principles of self-organization. However, despite all the evidence of positive prospects for the introduction of AOM technology the number of examples of its successful application to date is small. In this regard creation of new platforms for discussion of international experience and improvement of the approach to simulation modeling in general is especially important for further dissemination of AMB and MAS. Creation of an open consortium for agent-oriented modeling as well as promotion of development, communication and dissemination of research results as well as implementation of educational activities together will contribute to the development of agent based modeling. The analysis and review of existing methodology of social modeling with use of agent based approach in the application to scientific and technical development, implementation of R&D and maintenance of innovative potential showed that models characterized by complex multi-level processes and interactions of agents have more capacious software structures which depend more on the "fine" tuning of the agents themselves. Such models can contain and use a voluminous set of data, and in the field of economic research tend to focus on the analysis and forecasting of various socio-economic processes at the macro level.

show abstract

Section: модель инновационного развития отраслейunclassified

Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential

Abramov

Кудинов

Evdokimov

2019

Vestn. Voronež. gos. univ. inž. tehnol.

View full text Add to dashboard Cite

show abstract

“…Their model also accounts for characteristics that drive industries in their location decision, taking into account agglomeration forces. [4] In another model, Xie et al (2007) include growth linked to the development of the entire Wuxian City area in China. The units of analysis define the development of the land in the region.…”

Section: Earlier Applicationsmentioning

confidence: 99%

“…A determined area can be specialized in a "living" or "working" function. [4] In order to analyse the specialization, a computation of the number of workplaces per 100 residents is made. The following graph (Figure 4) shows the average degree of specialization for Switzerland and its sub-regions.…”

mentioning

confidence: 99%

Spatial Planning and Policy Evaluation in an Urban Conurbation: a Regional Agent-Based Economic Model

Stricker¹,

Baruffini²

2017

EoR

View full text Add to dashboard Cite

1 This paper studies different functions and relations between 45 agglomerated municipalities in southern Switzerland (Ticino), using a territorial agent-based model. Our research adopts a bottom-up approach to urban systems, considering the agglomeration mechanism and effects of different regional and urban policies, and simulates the individual actions of diverse agents on a real city using an Agent-based model (ABM). Simulating the individual actions of diverse agents on a real city and measuring the resulting system behaviour and outcomes over time, they effectively provide a good test bed for evaluating the impact of different policies. The database is created merging the Swiss official secondary data for one reference year (2011) with Eurostat and OECD-Regpat. The results highlight that the understanding of municipalities' functions on the territory appears to be essential for designing a solid institutional agglomeration (or city). From a methodo-

show abstract

“…Finally, the present model setup could be extended in a network setting, e.g., that of a downtown area or an inter-city network [26], to include a set of links with interdependent flows and explain macroscopic congestion phenomena. In that case, the dynamics of interaction among drivers moving in a specific road link, or a terrorist attack of one or several agents, would possibly affect the behavior of drivers moving at upstream links, for instance, through the delay propagation and cascading effects resulting from the formation of a downstream bottleneck.…”

Section: Concluding Remarks and Further Issuesmentioning

confidence: 99%

A Psycho-Social Agent-Based Model of Driver Behavior Dynamics

Tsekeris

Katerelos

2014

Springer Series in Reliability Engineering

Self Cite

View full text Add to dashboard Cite

This paper suggests a psycho-social agent-based model, referred to as Holistic-Emergent Social Interaction-Oriented Dynamics (HESIOD) model, to simulate the drivers' behavior dynamics under various types of interaction among vehicles. The HESIOD model allows representing the heterogeneity and dynamical processes involved in such control dimensions as risk assessment and time responsiveness of driving behavior (controlled dimension). It is shown that highly differentiated states may arise, such as fixed point, periodicity and transient chaos. The dynamical state is found to be mostly affected by the degree to which the control dimensions of neighboring vehicle drivers depart from each other, and the topology of interaction among drivers. In contrast with the aggregate statisticalprobabilistic models, this agent-based model can offer valuable insights into the role of both cognitive processes and interactions of drivers on their actual driving behavior. The findings may have useful implications for improving the level of service, safety and security in roads.

show abstract

Spatial agent-based modeling of household and firm location with endogenous transport costs

Abstract: Spatial agent-based models, System of cities, Location choices, Traffic congestion, Commuting, Migration, C63, R12, R23, R41, R53,

Cited by 13 publications

References 39 publications

Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential

Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential

Spatial Planning and Policy Evaluation in an Urban Conurbation: a Regional Agent-Based Economic Model

A Psycho-Social Agent-Based Model of Driver Behavior Dynamics

Contact Info

Product

Resources

About