Environment Mediated Multi Agent Simulation Tools &amp;#150; A Comparison

Global climate change affects marine fish through drivers such as ocean warming, acidification and oxygen depletion, causing changes in marine ecosystems and socioeconomic impacts. While experimental and observational results can inform about anticipated effects of different drivers, linking between these results and ecosystem‐level changes requires quantitative integration of physiological and ecological processes into models to advance research and inform management. We give an overview of important physiological and ecological processes affected by environmental drivers. We then provide a review of available modelling approaches for marine fish, analysing their capacities for process‐based integration of environmental drivers. Building on this, we propose approaches to advance important research questions. Examples of integration of environmental drivers exist for each model class. Recent extensions of modelling frameworks increase the potential for including detailed mechanisms and improving model projections. Experimental results on energy allocation, behaviour and physiological limitations will advance the understanding of organism‐level trade‐offs and thresholds in response to multiple drivers. More explicit representation of life cycles and biological traits can improve description of population dynamics and adaptation, and data on food web topology and feeding interactions help to detail the conditions for possible regime shifts. Identification of relevant processes will also benefit the coupling of different models to investigate spatial–temporal changes in stock productivity and integrated responses of social–ecological systems. Thus, a more process‐informed foundation for models will promote the integration of experimental and observational results and increase the potential for model‐based extrapolations into a future under changing environmental conditions.

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“…; Arunachalam et al . ). More specialized software tools model environmental impacts on the dispersal of planktonic fish larvae (Lett et al .…”

Section: From Processes To Models: Modelling Approaches and Their Capmentioning

confidence: 97%

Modelling climate change impacts on marine fish populations: process‐based integration of ocean warming, acidification and other environmental drivers

et al. 2016

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“…A number of reviews and surveys of ABMS tools/platforms have been undertaken (Abar, Theodoropoulos, Lemarinier, & O'Hare, 2017;Allan, 2010;Arunachalam & Steiner, 2008;Kravari & Bassiliades, 2015;Nikolai & Madey, 2009;Railsback, Lytinen, & Jackson, 2006;Tobias & Hofmann, 2004). The most recent of these reviews evaluates over eighty ABMS tools in terms of their respective technical features and specifications including model development effort and modeling strength (Abar et al, 2017).…”

Section: Selection Of Agent-based Modeling and Simulation Tool/platformmentioning

confidence: 99%

“…This review is described as providing guidance to potential users of these tools/platforms. Another review included NetLogo, MASON and Repast using assessment criteria related to design, model specification and execution, and documentation (Arunachalam & Steiner, 2008). Also, Repast and Swarm were considered in a review undertaken using a rating system including criteria such as documentation, support, user base and future viability (Tobias & Hofmann, 2004).…”

Section: Selection Of Agent-based Modeling and Simulation Tool/platformmentioning

confidence: 99%

“…In this paper, given the existence of the reviews undertaken, a summary is given of the key aspects of Repast (Michael J North, Collier, & Vos, 2006), specifically the Java-based Repast Simphony platform (M J North, 2005;Michael J North et al, 2013), leading to it being chosen to develop and implement the ABMS component of the framework in this research. A key feature of Repast is it was initially developed by social scientists to support applications in that domain (Allan, 2010;Arunachalam & Steiner, 2008;Railsback et al, 2006). Also, Repast provides demonstration simulation models and new users are supported by a community of model builders (Allan, 2010).…”

Section: Selection Of Agent-based Modeling and Simulation Tool/platformmentioning

confidence: 99%

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Agent-based modeling and simulation to assess flood preparedness and recovery of manufacturing small and medium-sized enterprises

Coates

Ahilan

et al. 2019

Engineering Applications of Artificial Intelligence

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“…Several computational platforms are currently available for the simulation/validation of bio-inspired models (e.g., SWARM, RePastS and NetLogo), in which the behaviors of biological entities (e.g., ants and bees) are usually implemented using software agents. (More information can be found in Railsback et al (2006) and Arunachalam et al (2008)). An interesting example is using the NetLogo platform to simulate the dynamic determination of the best path to route the products in situations with disturbances (Sallez et al, 2009).…”

Section: Applicability Of Bio-inspired Systems In Manufacturingmentioning

confidence: 99%

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

Leitão

Barbosa

Trentesaux

2012

Engineering Applications of Artificial Intelligence

135

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The current market's demand for customization and responsiveness is a major challenge for producing intelligent, adaptive manufacturing systems. The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized control approach. The MAS solutions provide modularity, flexibility and robustness, thus addressing the responsiveness property, but usually do not consider true adaptation and re-configuration. Understanding how, in nature, complex things are performed in a simple and effective way allows us to mimic nature's insights and develop powerful adaptive systems that able to evolve, thus dealing with the current challenges imposed on manufacturing systems. The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field. An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets.

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Environment Mediated Multi Agent Simulation Tools  A Comparison

Cited by 10 publications

References 4 publications

Modelling climate change impacts on marine fish populations: process‐based integration of ocean warming, acidification and other environmental drivers

Modelling climate change impacts on marine fish populations: process‐based integration of ocean warming, acidification and other environmental drivers

Agent-based modeling and simulation to assess flood preparedness and recovery of manufacturing small and medium-sized enterprises

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

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