Agent-based modelling for ecological economics: A case study of the Republic of Armenia

2017 ◽  
Vol 346 ◽  
pp. 99-118 ◽  
Author(s):  
Andranik S. Akopov ◽  
Levon A. Beklaryan ◽  
Armen K. Saghatelyan
Keyword(s):  
Ecological Economics ◽  
Agent Based ◽  
Agent Based Modelling ◽  
The Republic

scholarly journals Visualising Ostia’s Processional Landscape Through a Multi-Layered Computational Approach: Case Study of the Cult of the Magna Mater

2019 ◽  
Vol 5 (1) ◽  
pp. 444-467
Author(s):  
Katherine A. Crawford
Keyword(s):  
Network Analysis ◽  
Computational Approach ◽  
Urban Network ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Existing Problems ◽  
Layered Approach ◽  
Religious Landscape ◽  
Insight Into

AbstractOstia, the ancient port of Rome, had a rich religious landscape. How processional rituals further contributed to this landscape, however, has seen little consideration. This is largely due to a lack of evidence that attests to the routes taken by processional rituals. The present study aims to address existing problems in studying processions by questioning what factors motivated processional movement routes. A novel computational approach that integrates GIS, urban network analysis, and agent-based modelling is introduced. This multi-layered approach is used to question how spectators served as attractors in the creation of a processional landscape using Ostia’s Campo della Magna Mater as a case study. The analysis of these results is subsequently used to gain new insight into how a greater processional landscape was created surrounding the sanctuary of the Magna Mater.

A Comparison between Agent-Based and GIS-Based Tsunami Evacuation Simulations: A Case Study for Tofino, BC

2021 ◽  
Author(s):  
Joseph Kim ◽  
Tomoyuki Takabatake ◽  
Ioan NISTOR ◽  
Tomoya Shibayama
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Mortality Rates ◽  
Geographical Information ◽  
Evacuation Planning ◽  
Loss Of Life ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Validation Tool

Soft measures such as evacuation planning are recommended to mitigate the loss of life during tsunamis. Two types of evacuation models are widely used: (1) Agent-based modelling (ABM) defines sets of rules that individual agents in a simulation follow during a simulated evacuation. (2) Geographical information systems (GIS) are more accessible to city planners, but cannot incorporate the dynamic behaviours found in ABMs. The two evacuation modelling methodologies were compared through a case study by assessing the state of evacuation preparedness and investigating potential mitigation options. The two models showed different magnitudes for mortality rates and facility demand but had similar trends. Both models agreed on the best solution to reduce the loss of life for the community. GIS may serve as a useful tool for initial investigation or as a validation tool for ABMs. ABMs are recommended for use when modelling evacuation until GIS methodologies are further developed.

Improving the Efficiency of Large-Scale Agent-Based Models Using Compression Techniques

2012 ◽  
pp. 301-326
Author(s):  
Mitchell Welch ◽  
Paul Kwan ◽  
A.S.M. Sajeev ◽  
Graeme Garner
Keyword(s):  
Large Scale ◽  
Agent Based Models ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Livestock Disease ◽  
Interacting Agents ◽  
National Model ◽  
Complex Phenomena ◽  
Modelling System

Agent-based modelling is becoming a widely used approach for simulating complex phenomena. By making use of emergent behaviour, agent based models can simulate systems right down to the most minute interactions that affect a system’s behaviour. In order to capture the level of detail desired by users, many agent based models now contain hundreds of thousands and even millions of interacting agents. The scale of these models makes them computationally expensive to operate in terms of memory and CPU time, limiting their practicality and use. This chapter details the techniques for applying Dynamic Hierarchical Agent Compression to agent based modelling systems, with the aim of reducing the amount of memory and number of CPU cycles required to manage a set of agents within a model. The scheme outlined extracts the state data stored within a model’s agents and takes advantage of redundancy in this data to reduce the memory required to represent this information. The techniques show how a hierarchical data structure can be used to achieve compression of this data and the techniques for implementing this type of structure within an existing modelling system. The chapter includes a case study that outlines the practical considerations related to the application of this scheme to Australia’s National Model for Emerging Livestock Disease Threats that is currently being developed.

Agent-Based Modelling in Multicellular Systems Biology

2020 ◽  
pp. 369-389
Author(s):  
Sara Montagna ◽  
Andrea Omicini
Keyword(s):  
Developmental Biology ◽  
Drosophila Melanogaster ◽  
Systems Biology ◽  
Computational Models ◽  
The Self ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Multi Agent

This chapter aims at discussing the content of multi-agent based simulation (MABS) applied to computational biology i.e., to modelling and simulating biological systems by means of computational models, methodologies, and frameworks. In particular, the adoption of agent-based modelling (ABM) in the field of multicellular systems biology is explored, focussing on the challenging scenarios of developmental biology. After motivating why agent-based abstractions are critical in representing multicellular systems behaviour, MABS is discussed as the source of the most natural and appropriate mechanism for analysing the self-organising behaviour of systems of cells. As a case study, an application of MABS to the development of Drosophila Melanogaster is finally presented, which exploits the ALCHEMIST platform for agent-based simulation.

scholarly journals Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-24 ◽  
Author(s):  
Marc Deissenroth ◽  
Martin Klein ◽  
Kristina Nienhaus ◽  
Matthias Reeg
Keyword(s):  
Renewable Energy ◽  
Market Integration ◽  
Renewable Energy Sources ◽  
Policy Instruments ◽  
Energy Market ◽  
Agent Based ◽  
Policy Interactions ◽  
Agent Based Modelling ◽  
The Impact

The ongoing deployment of renewable energy sources (RES) calls for an enhanced integration of RES into energy markets, accompanied by a new set of regulations. In Germany, for instance, the feed-in tariff legislation for renewables has been successively replaced by first optional and then obligatory marketing of RES on competitive wholesale markets. This paper introduces an agent-based model that allows studying the impact of changing energy policy instruments on the economic performance of RES operators and marketers. The model structure, its components, and linkages are presented in detail; an additional case study demonstrates the capability of our sociotechnical model. We find that changes in the political framework cannot be mapped directly to RES operators as behaviour of intermediary market actors has to be considered as well. Characteristics and strategies of intermediaries are thus an important factor for successful RES marketing and further deployment. It is shown that the model is able to assess the emergence and stability of market niches.

scholarly journals A Theoretical Framework for Analysing Technology Transfer Processes Using Agent-Based Modelling: A Case Study on Massive Technology Adoption (AMTEC) Program on Rice Production

2021 ◽  
Vol 13 (20) ◽  
pp. 11143
Author(s):  
William Orjuela-Garzon ◽  
Santiago Quintero ◽  
Diana P. Giraldo ◽  
Laura Lotero ◽  
César Nieto-Londoño
Keyword(s):  
Technology Transfer ◽  
Technology Adoption ◽  
Production Costs ◽  
Analysis Tool ◽  
Transfer Program ◽  
Adoption Of Technology ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Productivity And Competitiveness

The technology transfer (TT) process has been studied from different approaches to improve productivity and competitiveness in agricultural chains. However, the process is not always presented successfully due to heterogeneity and inequality in the technological capacities (TC) of the agents that are part of the transfer process, in addition to the geographical context, the interaction networks and decision rules, which are key factors to understand the TT phenomenon. In this context and as a case study, the Colombian National Federation of rice growers promoted the development and adoption of technology that increased crop competitiveness and sustainability by implementing a technology transfer program known as the Massive Technology Adoption Program (AMTEC—Adopción Masiva de Tecnología) on rice. With the AMTEC program, average production costs were reduced by 26% (USD 119 per hectare), and it increased average yields by 23% (1.27 tonnes per hectare), which shows the importance of introducing technologies in productive chains in developing countries. This research provides a better understanding of the TT processes, based on the analysis of the interaction dynamics and behaviour patterns between the agents (i.e., generators, intermediaries, or users) in the TT processes. As an analysis tool, the agent-based modelling paradigm (ABM) was proposed to study the emergence at the macro-level of behaviour patterns of a system from the interactions of semi-intelligent agents at the micro-level, using experiments.

Cost-benefit analysis of demolition waste management via agent-based modelling: A case study in Shenzhen

2022 ◽  
Vol 137 ◽  
pp. 169-178
Author(s):  
Zhikun Ding ◽  
Xiaoyan Cao ◽  
Yifei Wang ◽  
Huanyu Wu ◽  
Jian Zuo ◽  
...  
Keyword(s):  
Waste Management ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Benefit Analysis ◽  
Demolition Waste ◽  
Agent Based ◽  
Agent Based Modelling

Biomimetic Agent Based Modelling Using Male Frog Calling Behaviour as a Case Study

2014 ◽  
pp. 88-97
Author(s):  
Søren V. Jørgensen ◽  
Yves Demazeau ◽  
Jakob Christensen-Dalsgaard ◽  
John Hallam
Keyword(s):  
Agent Based ◽  
Agent Based Modelling ◽  
Calling Behaviour
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