Using agent-based simulation to empirically examine search theory using a historical case study

Hill, Raymond R.; Carl, Ronald Gregory; Champagne, Lance

doi:10.1057/palgrave.jos.4250003

Cited by 22 publications

(14 citation statements)

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“…Following the conventional definition of simulation, we use the term ABMS in this article to refer to both agent-based simulation, in which a dynamic and timedependent process is modelled, and more general kinds of agent-based modelling that includes models designed to do optimization (see, eg, Olariu and Zomaya, 2006) or search (see, eg, Hill et al, 2006). For example, particle swarm optimization and ant optimization algorithms are both inspired by agent-based modelling approaches and are used to achieve an end (optimal) state rather than to investigate a dynamic process, as in a simulation.…”

Section: Agent-based Modellingmentioning

confidence: 99%

“…Applications range from modelling agent behaviour in the stock market (Arthur et al, 1997) and supply chains (Macal, 2004a) to predicting the spread of epidemics (Bagni et al, 2002) and the threat of bio-warfare (Carley et al, 2006), from modelling the adaptive immune system (Folcik et al, 2007) to understanding consumer purchasing behaviour (North et al, 2009), from understanding the fall of ancient civilizations (Kohler et al, 2005) to modelling the engagement of forces on the battlefield (Moffat et al, 2006) or at sea (Hill et al, 2006), and many others. Some of these applications are small but elegant models, which include only the essential details of a system, and are aimed at developing insights into a social process or behaviour.…”

Section: Introductionmentioning

confidence: 99%

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Tutorial on agent-based modelling and simulation

Macal

North

2010

Journal of Simulation

1,280

630

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Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling systems composed of autonomous, interacting agents. Agent-based modelling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modelling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.

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Section: Agent-based Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tutorial on agent-based modelling and simulation

Macal

North

2010

Journal of Simulation

1,280

630

View full text Add to dashboard Cite

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“…Existing applications of ABS for maritime search operations mainly focus on maritime patrol simulations to deter pirate attacks (Decraene et al 2010a, Bruzzone et al 2011, Jakob et al 2011, Tsilis 2011, Vaněk et al 2013, Marchione et al 2014, Dabrowski and De Villiers 2015, Varol and Gunal 2015, port-protection simulation (Leathrum et al 2009, Shieh et al 2012, Harris et al 2013, the simulation of traffic in ports and coastal waters (Hasegawa 2004), combat simulation (Champagne et al 2003, Price 2003, Cioppa et al 2004, Hill et al 2004, Champagne 2004, Hill et al 2006, Decraene et al 2010b, Xing et al 2013, surface surveillance simulations (Steele 2004) and force protection simulations (Harney 2003, Akbori 2004, Walton et al 2005, Sullivan 2006, Ng 2007. It is clear that most of the applications are for maritime security and military operations.…”

Section: Application Of Abs In Maritime Search Operationsmentioning

confidence: 99%

“…A simulation of the Bay of Biscay U-boat campaign has been reported several times (e.g. Champagne et al 2003, Champagne 2004, Hill et al 2004, Hill et al 2006. Champagne et al (2003) studied the emergent behaviours of combatants and the effectiveness of search patterns during the campaign.…”

Section: Application Of Abs In Maritime Search Operationsmentioning

confidence: 99%

Test-driven simulation modelling: A case study using agent-based maritime search-operation simulation

Onggo

Karataş

2016

European Journal of Operational Research

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Model verification and validation (V&V) is one of the most important activities in simulation modelling. Model validation is especially challenging for agent-based simulation (ABS). Techniques that can help to improve V&V in simulation modelling are needed. This paper proposes a V&V technique called Test-Driven Simulation Modelling (TDSM) which applies techniques from TestDriven Development in software engineering to simulation modelling. The main principle in TDSM is that a unit test for a simulation model has to be specified before the simulation model is implemented. Hence, TDSM explicitly embeds V&V in simulation modelling. We use a case study in maritime search operations to demonstrate how TDSM can be used in practice. Maritime search operations (and search operations in general) are one of the classic applications of Operational Research (OR). Hence, we can use analytical models from the vast search theory literature for unit tests in TDSM. The results show that TDSM is a useful technique in the verification and validation of simulation models, especially ABS models. This paper also shows that ABS can offer an alternative modelling approach in the analysis of maritime search operations. INTRODUCTIONAgent-Based Simulation (ABS) has become one of the commonly used tools to model and understand complex and nonlinear systems (North and Macal 2007). ABS provides a controlled environment for systematic experimentation using a simulation model that is formed from a set of interacting agents. There is no consensus on the definition of an agent in the ABS literature (Macal and North 2010). Instead, we have observed a spectrum of complexity in its definition. At one extreme, an ABS model is formed by a set of agents with a set of simple attributes (such as speed and detection range) and simple behaviours (such as move and rescue). At the other extreme, an ABS model can be composed of a set of agents with complex attributes (such as memory and bounded rationality) and complex abilities (such as planning and learning). However, most researchers agree that an agent is an autonomous entity (i.e. it makes independent decisions without any central control), has a set of objectives and interacts with other agents and its environment. One of the most important activities in ABS is model validation. There are similarities between ABS and Discrete-Event Simulation (DES). Both are able to represent stochastic dynamic systems and can track individuals' states throughout their lifecycles in the model. Hence, a number of validation techniques proposed for DES are also suitable for ABS, such as face validity, operational validity, white-box validation and black-box validation. Kleijnen (1995), Balci (1995 and Sargent (2013) provide a list of validation techniques in the context of stochastic dynamic simulation which are applicable to DES and ABS. All good simulation textbooks have at least one chapter that discusses validation techniques. Law (2014, chapter 5) and Banks et al. (2010, chapter 10) discuss various techniques...

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“…The existing applications of ABS for maritime search operations mainly focus on maritime patrol simulations to deter pirate attacks (Decraene et al 2010;Bruzzone et al 2011;Jakob et al 2011;Tsilis 2011;Jakob et al 2012;Vanek et al 2013), for port-protection simulation (Leathrum et al 2009;Shieh et al 2012), the simulation of traffic in ports and coastal waters (Hasegawa 2004), combat simulation (Champagne et al 2003;Price 2003;Cioppa et al 2004;Hill et al 2004;Hill et al 2006) and adversarial behaviour simulation (Agmon et al 2009;Jakob et al 2010). It is clear that most of the applications are for maritime security and military operations.…”

Section: Application Of Abs In Maritime Search Operationsmentioning

confidence: 99%

Agent-based model of maritime search operations: A validation using test-driven simulation modelling

Onggo¹,

Karataş²

2015

2015 Winter Simulation Conference (WSC)

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Mumtaz Karatas Department of Industrial EngineeringTurkish Naval Academy Tuzla, Istanbul, 34942, TURKEY Maritime search operations (and search operations in general) are one of the classic applications of Operational Research (OR). This paper presents a generic agent-based model for maritime search operations which can be used to analyse operations such as search and rescue and patrol. Agent-based simulation (ABS) is a relatively new addition to existing OR techniques. The key elements of an ABS model are agents, their behaviours and their interactions with other agents and the environment. A search operation involves at least two types of agent: a searcher and a target. The unique characteristic of ABS is that we model agents' behaviours and their interactions at the individual level. Hence, ABS offers an alternative modelling approach to analyse search operations. The second objective of our work is to show how test-driven simulation modelling (TDSM) can be used to validate the agent-based maritime search operation model. 1 978-1-4673-9743-8/15/$31.00 ©2015 IEEE

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Using agent-based simulation to empirically examine search theory using a historical case study

Cited by 22 publications

References 4 publications

Tutorial on agent-based modelling and simulation

Tutorial on agent-based modelling and simulation

Test-driven simulation modelling: A case study using agent-based maritime search-operation simulation

Agent-based model of maritime search operations: A validation using test-driven simulation modelling

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