Agent Based Simulation Research Papers (original) (raw)

This paper investigates the effectiveness of an agent based trading system. The system developed employs a simple genetic algorithm to evolve an optimized trading approach for every agent, with their trading decisions based on a range of technical indicators generating trading signals. Their trading pattern follows a simple fitness function of maximizing net assets for every evolutionary cycle. Their performance is analyzed compared to market movements as represented by its Index, as well as investment funds run by human professionals to establish a relative measure of success. The results show that the developed system performs comparably to its human counterparts across different market environments, despite these agents being rather primitive in nature. Future forthcoming work will refine and explore the potential of this approach further.

- by and +1
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- Genetic Algorithms, Agent Based Simulation, Capital Markets
- by Carolina Cantergiani
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- Agent Based Simulation, Urban Growth, Agent Based Models, Urban Planner

This paper describes the development of a generalized agent -based simulation tool for studying manpower and personnel management behaviors. The subject matter of the simulation are complex organizational behaviors found within Uni ted States Navy Manpower and Personnel processes. Behavior of such a complex system is typically associated with a hierarchi- cal structure in which the lowest level agents are

- by Denis Garagic
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- Organizational Behavior, Decision Making, Systems Engineering, Fuzzy Logic

development of an efficient real the areas where security is the main concern. The proposed system presents a platform for r detection and subsequent generation of an alarm condition as soon as the human head is detected. The prototype consists of a platform mounted with a camera that provides continuous feedback of the online exam environment. Keywords Nowadays several problems exist in human head motion analysis and this includes: Unable to provide an optimal method of dimensionality reduction to achieve a higher recognition rate.10 Human head done (from the training set) by combining the Eigenfaces alone. The weighting factors need to be more adaptive to achieve better results. Less scalability exists for detecting human head motion. Image block matching, gradient cons Intelligent video surveillance systems are receiving a great deal of interest especially in the fields of personal security and assistance. These systems are built in order to accomplish presence to recognition of their activities. In the past few decades, vision applied to industrial inspection, traffic control, security systems, and medical and scientific resea application areas of video surveillance is monitoring the safety of the elderly in home environments. In the case of elderly people living on their own, there is a particular need for monitoring their behaviour, such as a fall, or a long period of inactivity. Fall in the elderly is a major public health problem and may lead to injury, restricted activities, fear of death. A fall incident not also causes many disabling fractures but also has dramatic psychological consequences that reduce the It is shown that 28 the falls lead to injury. Human society is experiencing tremendous demographic changes in aging since the turn o the 20th century. The ability to help elderly people. Nowadays, the usual solution to detect falls is wearable sensors [These autonomous sensors are usually attached under the armpit, around the wrist, behind the ear's lobe or at the waist. Moreover, in Although, computer vision systems try to extract some considerable features from video sequences of movement patterns to detect falls. The data provided by sensors.

Deregulated electricity markets are expected to provide affordable electricity for consumers through promoting competition. Yet, the results do not always fulfill the expectations. The regulator's market-clearing mechanism is a strategic choice that may affect the level of competition in the market. We conceive of the market-clearing mechanism as composed of two components: pricing rules and rationing policies. We investigate the strategic behavior of power generation companies under different market-clearing mechanisms using an agent-based simulation model which integrates a game-theoretical understanding of the auction mechanism in the electricity market and generation companies' learning mechanism. Results of our simulation experiments are presented using various case studies representing different market settings. The market in simulations is observed to converge to a Nash equilibrium of the stage game or to a similar state under most parameter combinations. Compared to pay-as-bid pricing, bid prices are closer to marginal costs on average under uniform pricing while GenCos' total profit is also higher. The random rationing policy of the ISO turns out to be more successful in achieving lower bid prices and lower GenCo profits. In minimizing GenCos' total profit, a combination of pay-as-bid pricing rule and random rationing policy is observed to be the most promising.

- by Danial Esmaeili Aliabadi
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- Game Theory, Reinforcement Learning, Agent Based Simulation, Pricing

This paper explores the role of gaze in coordinating turn-taking in mixed-initiative conversation and specifically how gaze indicators might be usefully modeled in computational dialogue systems. We analyzed about 20 minutes of videotape... more

- by Brian Hansen
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- Computational Modeling, Agent Based Simulation, Dialogue System, Speech acts

HIV/AIDS is a key concern in South Africa. However, its impact cannot be examined in isolation of other stresses, such as food insecurity, high climate variability, market fluctuations, and poor governance. In this paper, we present an agent-based simulation model of the social impacts of HIV/AIDS in villages in the Vhembe district, Limpopo Province, South Africa. It has been developed in the context of the CAVES (Complexity, Agents, Vulnerability, Evidence, and Scale) project. It is our understanding that modelling the complex interactions at the individual and household level will enable stakeholders to better understand the impact of stressors and potential coping strategies at the community level. The model and its preliminary results are presented to motivate discussion among the social science community.

- by Shah Jamal Alam
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- Social Networks, Coping Strategies, Climate variability, Agent Based Simulation

The study of material culture generated by military engagements has created an emergent sub-discipline of archaeological studies centred on battlefields. This approach has developed a particular and sophisticated methodology that is able to deal with the fact that archaeologists will often not find either structures or a useful stratigraphical record on the site, as the material remains of the battle

En la actualidad existe una preocupación global sobre el impacto ambiental de la actividad humana en general -y agropecuaria en particular-, con atención en el flujo de
macronutrientes como el N (Schlesinger, 2009). En sistemas de producción intensivos
como es la lechería, la dinámica del N es un aspecto para profundizar, complejizándose el análisis al considerar su dinámica espacial y temporal. Por otra parte, y en términos generales, los modelos de simulación permiten formalizar y analizar el problema de la sustentabilidad (Thompson, 2007). En particular el modelado multiagente (ABM) tiene la ventaja de la espacialización del problema, donde la interacción entre agentes puede ser representada y evaluada dinámicamente (Railsback & Grimm, 2019). El ABM puede representar interacciones complejas dentro de los socio-ecosistemas (Grimm et al., 2010), reproduciendo reglas de manejo e interacción entre los agentes posibilitando un análisis global de todo el sistema, como local de cada agente (animales, parcelas y sistema de efluentes). Este trabajo presenta un estudio de caso donde se realizó una primera implementación de un modelo de simulación para caracterizar el flujo de N y su dinámica espacial y temporal, aplicando el concepto ABM, ya que este elemento presenta varios
compuestos con impacto ambiental, como lo son la emisión de óxido nitroso y la
lixiviación de nitratos a aguas superficiales y profundas, tanto a escala de sistema de
tratamiento de efluentes como en parcela.

- by Francisco Dieguez and +1
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- Agent Based Simulation, Nutrient budgets and exportation
- by Wayne Wakeland
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- Information Systems, Game Theory, Knowledge Management, Agent Based Simulation

Agent-based social simulations are typically described in imperative form. While this facilitates implementation as computer programs, it makes implicit the different assumptions made, both about the functional form and the causal ordering involved. As a solution to the problem, a probabilistic graphical model, Action Network (AN), is proposed in this paper for social simulation. Simulation variables are represented by nodes, and causal links by edges. An Action Table is associated with each node, describing incremental probabilistic actions to be performed in response to fuzzy parental states. AN offers a graphical causal model that captures the dynamics of a social process. The details of the formalism are presented, along with illustrative examples. A software implementing the formalism is available in http://actionnetwork.epizy.com.

- by nordin zakaria
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- Agent Based Simulation, Causal reasoning, Social Simulation, Agent-based modeling

We present evidence for the importance of low-level phenomena in dialogue interaction and use this to motivate a multi-layered approach to dialogue processing. We describe an architecture that separates content-level communicative processes from interaction-level phenomena (such as feedback, grounding, turn-management), and provide details of specific implementations of a number of such phenomena.

Diplomová práce se zabývá multiagentním modelováním (ABM, počítačová simulační
metoda) vycházejícím z konceptu analytické sociologie a jeho využitím v empirické
sociologii. Využití je demonstrováno tvorbou modelu založeném na principech
environmentální sociologie zkoumající vliv sociálních faktorů na životní prostředí. Práce
vychází z empiricko-teoretického konceptu Nové ekologické paradigma (NEP), které
měří hodnoty a názory na životní prostředí. Vznik práce byl motivován absencí projektů
snoubících metodu empiricky kalibrovaného multiagentního modelování a sociologický
základ, zejména v českém kontextu, ale převážně i v zahraničí. Na základě
environmentálního modulu českých dat ISSP 2010 a výzkumné otázky „Jak parametry
sociální sítě ovlivňují ochotu lidí třídit odpad?“ byl vytvořen a následně i analyzován
model. Byl nalezen vztah mezi oběma typy agentů (třídícími i netřídícími během celé
simulace) a jejich bezprostředním okolím (sousedy). Čím větší byl počet sousedů, tím
více se vyskytovalo agentů s tímto typem chování. Pravděpodobnost vytvoření pouta se
vzdálenějším sousedem na úkor zrušení blízké vazby se ukázala být bez vlivu na počet
ne/třídících agentů. Zdá se tedy, agenti mají tendence replikovat jednání svých sousedů
v bezprostředním okolí, aby se v něm mohli cítit komfortně.

- by Michaela Prokeš
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- Sociology, Environmental Sociology, Agent Based Simulation

Formal models of scientific inquiry, aimed at capturing socio-epistemic aspects underlying the process of scientific research, have become an important method in formal social epistemology and philosophy of science. In this introduction to the special issue we provide a historical overview of the development of formal models of this kind and analyze their methodological contributions to discussions in philosophy of science. In particular, we show that their significance consists in different forms of 'methodological iteration' (Elliott, 2012) whereby the models initiate new lines of inquiry, isolate and clarify problems with existing knowledge claims, and stimulate further research. Throughout the last two decades philosophical discussions on scientific inquiry have increasingly utilized formal models. This has been especially fruitful for the investigation of social aspects of scientific inquiry, such as the division of cognitive labor, the epistemic effects of scientific interaction, the impact of biases on scientific research, etc. To this end a variety of formal models have been developed, from analytical ones to computer simulations in the form of agent-based models. One of the main advantages of formal approaches is that, in principle, they can help us to gain a precise understanding of the underlying issues and to form normative generalizations that are difficult to obtain in view of traditional methods (such as, for example, historical case studies). Nevertheless, models frequently come with a high degree of idealization and simplification, which may impede their reliability concerning actual scientific practice. This poses the question, to which 1

- by Dunja Šešelja and +2
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- Agent Based Simulation, Agent-based modeling, Scientific Inquiry

Belief-Desire-Intention (BDI) model is well suited for describing agent’s mental state. The BDI of an agent represents its motivational stance and are the main determinant of agent’s actions. Therefore, explicit understanding of the representation and modelling of such motivational stance plays a central role in designing BDI agent with successful behavioural change interventions. Nevertheless, existing BDI agent models do not represent agent’s behavioural factors explicitly. This leads to a gap between design and implementation where psychological reactance has being identified as the cause of BDI agent behavioural change interventions failure. Hence, this paper presents a generic representation of BDI agent model based on behavioural change and psychological theories. The objective of this proposed BDI agent model is to bridge the gap between agent design and implementation for successful agent-based interventions. The model will be realized in an agent-based application that motivates children towards oral hygiene.

- by Adegoke Ojeniyi and +1
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- Behavioral Sciences, Agent Based Simulation, Modeling and Simulation, (Multi-) Agent Technology
- by Blesson Varghese
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- Robotics, Multiagent Robotics, Autonomous Robotics, Agent Based Simulation

This paper develops and simulates a model of emergence of networks in an interbank, RTGS payment system. A number of banks, faced with random streams of payment orders, choose whether to link directly to the payment system, or to use a correspondent bank. Settling payments directly via the system imposes liquidity costs, which depend on the maximum liquidity overdraft incurred during the day. On the other hand, using a correspondent entails paying a flat fee, charged by the correspondent to recoup liquidity costs and to extract a profit. We specify a protocol whereby banks sequentially choose whether to link directly to the system or to become clients of other banks, thus generating a client-correspondent network. We calibrate our model on real data on the UK payment system, and we compare the networks it produces with i) the true client-correspondent network, ii) the outcomes of two ‘dummy' benchmark models. The model is found to outperform the benchmarks. Its predicted network...

- by Marco Galbiati
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- Business, Agent Based Simulation, Networks, Agent-Based Computational Economics

We present a fully procedural alternative to branching dialogue that is influenced by theories from linguistic pragmatics and technical work in the field of dialogue systems. Specifically, this is a dialogue manager that extends the Talk of the Town framework, in which non-player characters (NPCs) develop and propagate subjective knowledge of the gameworld. While previously knowledge exchange in this framework could only be expressed symbolically, such exchanges may now be rendered as naturalistic conversations between characters. The larger conversation engine currently lacks a player interface, so in this paper we demonstrate our dialogue manager through conversations between NPCs. From an evaluation task, we find that our system produces conversations that flow far more naturally than randomly assembled ones. As a design objective, we have endeavored to make this dialogue manager lightweight and agnostic to its particular application in Talk of the Town; it is our hope that interested readers will consider porting its straightforward design to their own game engines.

- by James Ryan
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- Artificial Intelligence, Natural Language Generation, Multiagent Systems, Video Games
- by Mehmet Fatih Hocaoğlu
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- Computer Science, Agent Based Simulation, Industry, Wargames

We built a multiagent simulation of urban traffic to model both ordinary traffic and emergency or crisis mode traffic.
This simulation first builds a modeled road network based on detailed geographical information. On this network, the simulation creates two populations of agents: the Transporters and the Mobiles. Transporters embody the roads themselves; they are utilitarian and meant to handle the low level realism of the simulation. Mobile agents embody the vehicles that circulate on the network. They have one or several destinations they try to reach using initially their beliefs of the structure of the network (length of the edges, speed limits, number of lanes etc.). Nonetheless, when confronted to a dynamic, emergent prone environment (other vehicles, unexpectedly closed ways or lanes, traffic jams etc.), the rather reactive agent will activate more cognitive modules to adapt its beliefs, desires and intentions. It may change its destination(s), change the tactics used to reach the destination (favoring less used roads, following other agents, using general headings), etc.
We describe our current validation of our model and the next planned improvements, both in validation and in functionalities.

Institutional frameworks powerfully determine the goals, violence, and trajectories of identitarian movements—including secessionist movements. However, both small-N and large-N researchers disagree on the question of whether “power-sharing” arrangements, instead of repression, are more or less likely to mitigate threats of secessionist mobilizations by disaffected, regionally concentrated minority groups. The PS-I modeling platform was used to create a virtual country “Beita,” containing within it a disaffected, partially controlled, regionally concentrated minority. Drawing on constructivist identity theory to determine behaviors by individual agents in Beita, the most popular theoretical positions on this issue were tested. Data were drawn from batches of hundreds of Beita histories produced under rigorous experimental conditions. The results lend support to sophisticated interpretations of the effects of repression vs. responsive or representative types of power-sharing. Although in the short run repression works to suppress ethnopolitical mobilization, it does not effectively reduce the threat of secession. Power-sharing can be more effective, but it also tends to encourage larger minority identitarian movements.

- by Dan Miodownik
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- Constructivism, Agent Based Simulation, Secession, Agent-based modeling

Agent Based Modeling and Simulation (ABMS) is an effective and trustful method to solve the complex problems of today’s world. High competition in international markets, reduced product life cycle, and increased customer requirements are the key factors, which have made supply chain to be used widely in recent years. In today's complex business environment, according to the factors such as supply chain globalization, increased outsourcing, increased fluctuations in supply and demand, and short product life cycles, firms face with a greater need for supply chain risk management (SCRM). This paper aims to study the literature of ABMS to analyze SCRM since 2000 until now, specially, the newest. Dealing with the works done on ABMS and SCRM, separately, we will discuss the literature of using ABMS in SCRM. Studies show that the issue has attracted more attention, today (nowadays). Hence, it is interesting to establish the appropriate context to conduct more analyzes in the areas that currently have limitations

Islamic banking has come to the forefront as being one of the fastest growing branch of the global financial industry in recent years. In this study we evaluate whether coexistence of Islamic and conventional banks promote financial stability. In this respect, we evaluate two types of financial systems: (1) A system solely comprised of conventional banks, (2) a dual system in which conventional and Islamic banks coexist and interact with each other. Accordingly, we design two agent-based models representing aforementioned systems and examine possible contagious effects and causes of bank failures by employing the volatility spillover methodology. We find that Islamic banks greatly promote stability by providing liquidity during financial shocks and create more liquidity per asset compared to conventional banks. We also find that they tend to hold more cash than conventional banks, which cushion the effects of a possible liquidity squeeze. Conventional banks, on the other hand, tend ...

and watch. During the top) service has seen an exponential a growing activity and on this field. In past few Paper, human emotions to provide dynamic content recommen deep list of movies overcome problem in existing method. Keywords When television first came player emerge in the market. with the introduction of the Netflix, Amazon Prime and many other OTT(Over the top) media around provides the has changed the way users interact with video content. films and human emotions. Emotions neurophysiologic pleasure or displeasure. The recent advancement in machine learning, Computer vision and recommendation has achieved studies on computer vision, there is a possibility of improving the quality of Recommendation System whose primary goal is to predict predictions we decide whether to learning have become very popular target their content to a specific audience. they can d The motivation in this work to use emotion technique in recommendation system to generate additional input movie recommendation system a system,

With progressively increased people living in cities, and lately the global COVID-19 outbreak, human mobility within cities has changed. Coinciding with this change, is the recent uptake of the '15-Minute City' idea in urban planning around the world. One of the hallmarks of this idea is to create a high quality of life within a city via an acceptable travel distance (i.e., 15 minutes). However, a definitive benchmark for defining a '15-Minute City' has yet to be agreed upon due to the heterogeneous character of urban morphologies worldwide. To shed light on this issue, we develop an agent-based model named 'D-FMCities' utilizing realistic street networks and points-of-interest, in this instance the borough of Queens in New York City as a test case. Through our modeling we grow diverse communities from the bottom up and estimate the size of such local communities to delineate 15-minute cities. Our findings suggest that the model could be helpful to detect the flexibility of defining the extent of a '15-minute city' and consequently support uncovering the underlying factors that may affect its various definitions and diverse sizes throughout the world.

- by Rick Dale
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- Applied Mathematics, Language Acquisition, Agent Based Simulation, Complex Systems

La circulation de piétons dans un bâtiment exige une conception strictement effective afin de réduire au minimum les bouchons (embouteillages) potentiels qui pourraient accroître à la fois le temps d'évacuation et le risque de blesser la foule. Les catastrophes souvent impliquant des évacuations de la foule amènent à une nécessité d'une analyse rigoureuse de la circulation de la foule via la simulation. Ces tragédies ont pour la plupart impliquées l'écrasement de la foule ou de l'échec d'échappement d'un bâtiment en raison de la congestion, mais la modélisation des piétons ne doit pas être limitée juste à ce scénario. La circulation des piétons est en train de devenir un facteur important dans la conception des bâtiments.

- by Hoc Ine
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- Artificial Intelligence, Agent Based Simulation, Artificial Life, Simulation

Recent studies of scientific interaction based on agent-based models
(ABMs) suggest that a crucial factor conducive to efficient inquiry is what Zollman, 2010 has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories
lasting sufficiently long for the community to identify the best theory and
to converge on it. But what exactly generates transient diversity? And
is transient diversity a decisive factor when it comes to the efficiency of
inquiry? In this paper we examine the impact of different conditions on
the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature (such as different social networks and cautious decision-making), as well as some factors that have so far been neglected (such as evaluations underlying theory-choice performed by scientists). This study is obtained via an argumentation-based ABM (Borg et al., 2017, 2018). Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model.

- by AnneMarie Borg and +3
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- Social Networks, Agent Based Simulation, Robustness Analysis, Argumentation Theory
- by Fernando Aguiar
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- Agent Based Simulation, TOLERANCIA
- by Pawel Sobkowicz
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- Human Factors, Web Mining, Agent Based Simulation, Content Analysis

Bu çalışmada, paralel simülasyonda işletim zamanlı senkronizasyon algoritması seçimini zeki olarak yürüten bir dağıtık simülasyon model kütüphanesi geliştirilmiştir. Etmen olarak tasarlanan simülasyon modeli (DS-a) ve senkronizasyon algoritmaları ile, bir ağ üzerinde herhangi bir merkezi koordinasyon bağımlılığı olmadan, işletim sağlanmıştır.
DS-a yönetimini üstlendiği simülasyon modellerinin simülasyon servislerini yürütürken, koşum performansını en iyileyecek senkronizasyon algoritmalarını kural tabanlı olarak seçmektedir. Simülasyon yönetiminin modeller aracılığı sağlanması önemli bir esneklik sağlamıştır. Etmen Tabanlı Simülasyon Sistemi (EtSiS) tarafından desteklenen çoklu programlama paradigmaları ile sağlanan güçlü programlama arkaplanı ve dağıtık simülasyonda dinamik olarak simülasyon senkronizasyonunun bir otonom etmen ile gerçekleştirilmesi, çalışmanın merkezi yenilikleri olarak görülmektedir.
In this study, a simulation model library that choices synchronization algorithms for parallel simulation in execution time is developed. Using the model that is developed as an agent named DS-a and a series of synchronization algorithms, simulation executions are achieved on a network without any centralized coordination.
While DS-a provides simulation services to simulation models it is in charge of, it also choices simulation synchronization algorithms to maximize execution performance as rule based. Managing simulation execution by simulation models provides a distinguished flexibility. The powerful programming background that are provided by multi programming paradigms supported by Agent driven simulation framework – AdSiF and parallel simulation execution synchronization by an autonomous agent are the central concepts of the study.

Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inherently interested in an interdisciplinary comparison of models, to the best of our knowledge, there is currently no single unified framework for facilitating the development, comparison, communication and validation of models across different scientific domains. In this thesis, we propose first steps towards such a unified framework using a combination of agent-based and complex network-based modeling approaches and guidelines formulated in the form of a set of four levels of usage, which allow multidisciplinary researchers to adopt a suitable framework level on the basis of available data types, their research study objectives and expected outcomes, thus allowing them to better plan and conduct their respective research case studies. Firstly, the complex network modeling level of the proposed framework entails the development of appropriate complex network models for the case where interaction data of cas components is available, with the aim of detecting emergent patterns in the cas under study. The exploratory agent-based modeling level of the proposed framework allows for the development of proof-of-concept models for the cas system, primarily for purposes of exploring feasibility of further research. Descriptive agent-based modeling level of the proposed framework allows for the use of a formal step-by-step approach for developing agent-based models coupled with a quantitative complex network and pseudocode-based specification of the model, which will, in turn, facilitate interdisciplinary cas model comparison and knowledge transfer. Finally, the validated agent-based modeling level of the proposed framework is concerned with the building of in-simulation verification and validation of agent-based models using a proposed Virtual Overlay Multiagent System approach for use in a systematic team-oriented approach to developing models. The proposed framework is evaluated and validated using seven detailed case study examples selected from various scientific domains including ecology, social sciences and a range of complex adaptive communication networks. The successful case studies demonstrate the potential of the framework in appealing to multidisciplinary researchers as a methodological approach to the modeling and simulation of cas by facilitating effective communication and knowledge transfer across scientific disciplines without the requirement of extensive learning curves.

A simulation model is a copy of a real world system on computer and can be used to see results of different scenarios. But, simulation modeling typically requires some training and learning, in a conclusion it’s harder than mathematical models. There are three simulation methods: Discrete Event Simulation (DE), Agent-Based Simulation (AB) and System Dynamics (SD). The example is a scenario in healthcare sector. Finally, results of the example will be shown with graphical methods.

- by Gizem Güneş
- •
- Agent Based Simulation

Agent-Based Modeling is a research method that represents theories of social behavior as computer programs of a particular kind, rather than narratives (as ethnography does) or equations (as regression models do). Like existing research methods in sociology (both qualitative and quantitative) it can be applied throughout the discipline and offers advantages for certain research questions. In particular, the approach is referred to as agent-based because the computer program unambiguously represents interactions between heterogeneous social actors while also explicitly determining their aggregate simulated consequences. This distinguishes Agent-Based Modeling from existing quantitative approaches in sociology where the relationship between aggregate associations and individual agency is often unclear. It also distinguishes the method from existing qualitative approaches that, while investigating individuals and their interactions, have no systematic techniques for establishing their aggregate consequences. Given this capability, the methodology of Agent-Based Modeling has a distinctive logic. Agent-Based Models are calibrated using data on individual behavior (for example using ethnography or laboratory experiments) and then the computer program generates simulated aggregate data. This can then be compared with equivalent real data for validation. It is the independence of these two activities that provides Agent-Based Modeling with its distinctive claim to explanatory power. The explicitly represented link between individual and aggregate respects the complexity of social systems, the phenomenon in which individuals and their simple interactions may produce surprisingly counter-intuitive aggregate outcomes. Agent-Based Models are thus particularly suitable for investigating sociological issues involving heterogeneous actors, diverse cognitive processes and social systems mediated by entities operating between the level of the individual and the aggregate (like schools and churches).

- by Edmund Chattoe-Brown
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- Sociology, Psychology, Economics, Research Methodology

Wireless Sensor Networks (WSN) are a fast-emerging area of interest in the domain of large-scale communication networks. However, design of novel WSN applications requires first developing models and performing extensive
simulation. Modern large-scale WSNs are expected to be both dynamic as well as random and often spread over a large scale. However, this problem has not previously been addressed in literature. In our previous works, we have demonstrated how Agent-based modeling may be used to effectively model various types of Complex Adaptive Systems such as, but not limited to, Self-organizing Communication infrastructures. In this paper, we present first steps towards providing a comprehensive set
of guidelines and tutorial for developing deployment models of WSNs besides modeling routing algorithms using agent-based modeling. Our simulation results demonstrate the effectiveness and ease of use coupled with a short learning curve involved in developing agent-based models of complex WSN applications.

- by Muaz A Niazi and +1
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- Wireless Communications, Agent Based Simulation, The Internet of Things, Wireless Sensor Networks
- by Dirk Pijpops
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- Historical Linguistics, Agent Based Simulation

This chapter picks up where the “wicked problems team” left off in Venturing Beyond the Classroom: with the need to formulate effective teaching strategies for an exceptionally im- portant area of inquiry, in which our understanding is, as yet, far short of perfection. Docherty and Lira are examples of professionals whose students cannot wait for anything close to perfection: both in peacebuilding and in the military, a professional must work with the understanding that is available. It is significant that in their very dif- ferent environments, Docherty and Lira have been learning from each other, adapting ideas from the military into peacebuilding and vice versa, in order to formulate teaching programs that can work even within the single perspective of either discipline. Their experiments are groundbreaking, and of importance to many other professional fields.

- by Jayne S . Docherty
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- Teaching and Learning, Agent Based Simulation, Pedagogy, Negotiation

In this paper, we are presenting a number of research projects, which illustrate a design methodology developed by Research Cluster 6 (RC6) of The Bartlett's Graduate Architectural Design program, positioned on the overlap between the digital (agent-based design strategies and generative form-finding) and analogue computation strategies (material behaviour and crafting techniques). In that context, RC6's agenda argues for a new kind of craft, rooted in a thorough understanding of traditional, hands-on craft combined with expertise in contemporary computational concepts. In this regard, research presented in this paper primarily focuses on merging traditional, low-tech manufacturing processes with advanced technological approaches to design and realise new spatial concepts. Particular interest lies in novel combinations of analogue and digital methods in which hands-on and computer-controlled design and manufacturing operations do not just co-exist but overlap. The two projects presented in this paper, SanDPrint and FaBrick, address these premises through custom developed form-finding and fabrication processes, and test them through 1:1 scale prototypes.

- by Soomeen Hahm and +1
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- Agent Based Simulation, Generative Architectural Design

Una gran parte de las pequeñas y medianas empresas Colombianas han mostrado, de acuerdo con cifras oficiales, unos muy bajos índices de supervivencia tras sus primeros años de creación. Esto es especialmente grave dado que dichas empresas son las que proveen la mayor parte del empleo formal del país, poniendo también en perspectiva los efectos futuros de los nuevos tratados de libre comercio. Considerando la urgencia de brindarle a los empresarios Colombianos herramientas que les permita mejorar la productividad de sus empresas para afrontar mejor la competencia extranjera, en este artículo se presenta una herramienta de simulación de procesos de manufactura diseñada específicamente para ayudar a la transferencia de la metodología de mejoramiento contínuo TOC (teoría de restricciones) a la pequeña y mediana empresa, y a mitigar uno de los mayores riegos asociados a esta tarea: la resistencia al cambio. Abstract The small and medium enterprise in Colombia have shown, according to official statistics, a very low survival rate after its first years of creation. This is specially worrying given that such enterprises provide most of the formal employment in the country, and also considering the perspective of the future effects of the new free-trade agreements. Given the urgency of providing to the entrepreneurs tools that would let them improve their companies' productivity, this paper presents a simulation tool for manufacturing processes proposed to support the transfer of the TOC (Theory of Constraints) continuous improvement methodology to the small and medium enterprises, and to mitigate one of the largest risks of such transference: the change resistance.

- by Héctor F Cadavid and +1
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- Agent Based Simulation, Teoria De Restricciones

Public Participation in transport planning is often regarded as a formal compulsory phase of the decision-making process and it lacks in its real purpose, i.e. engaging people to find the most shared solution in the shortest time, in order to make the process effective and (cost) efficient.
The need to include the public in transport planning and decision-making leads to the effort to understand how to design and speed up the process of taking a public decision and to find out if the communication among stakeholders can influence the process of governance. In this paper an agent-based model is presented as a contribution to build new tools to support decision-makers and practitioners in designing and guiding effective participation processes. The model reproduces the interaction process in a network of stakeholders by means of a multi-state opinion dynamics and bounded confidence model as a basis to investigate the consensus formation phenomenon. The participatory decision-making process about the acceptability of a parking management strategy inside a University campus in Catania (Italy) was simulated to see to what extent interaction among stakeholders can foster the emergence of consensus. A better parking management is one of the priorities for sustainable mobility proposed by the mobility management office of the University. Results show that many links can help the opinion exchange process and the convergence of opinions and that the final outcome (i.e. approval or disapproval of the parking
management strategy) is highly influenced by the initial distribution of opinions. This suggests that having a preliminary knowledge of stakeholders’ opinions can be helpful to arrange the participation process and repeated interaction opportunities contribute in smoothing diverging opinions.

- by Michela Le Pira and +1
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- Agent Based Simulation, Transport Planning, Transportation Policy, Public Participation In Governance

The goal of this thesis is twofold. First, intention recognition is studied from an Artificial Intelligence (AI) modeling perspective. We present a novel and efficient intention recognition method that possesses several important features: (i) The method is context-dependent and incremental, enabled by incrementally construct- ing a three-layer Bayesian Network model as more actions are observed, and in a context-dependent manner, relying on a logic programming knowledge base concern- ing the context; (ii) The Bayesian Network is composed from a knowledge base of readily specified and readily maintained Bayesian Network fragments with simple structures, enabling an efficient acquisition of the corresponding knowledge base (ei- ther from domain experts or else automatically from a plan corpus); and, (iii) The method addresses the issue of intention change and abandonment, and can appro- priately resolve the issue of multiple intentions recognition. Several aspects of the method are evaluated experimentally, achieving some definite success. Furthermore, on top of the intention recognition method, a novel framework for intention-based decision making is provided, illustrating several ways in which an ability to recognize intentions of others can enhance a decision making process.
A second subgoal of the thesis concerns that, whereas intention recognition has been extensively studied in small scale interactive settings, there is a major shortage of modeling research with respect to large scale social contexts, namely evolution- ary roles and aspects of intention recognition. Employing our intention recognition method and the tools of evolutionary game theory, this thesis explicitly addresses the roles played by intention recognition in the final outcome of cooperation in large populations of self-regarding individuals. By equipping individuals with the capacity for assessing intentions of others in the course of social dilemmas, we show how in- tention recognition is selected by natural selection, opening a window of opportunity for cooperation to thrive, even in hard cooperation prone games like the Prisoner’s Dilemma.
In addition, there are cases where it is difficult, if not impossible, to recognize the intentions of another agent. In such cases, the strategy of proposing commitment, or of intention manifestation, can help to impose or clarify the intentions of others. Again using the tools of evolutionary game theory, we show that a simple form of commitment can lead to the emergence of cooperation; furthermore, the combination of commitment with intention recognition leads to a strategy better than either one by itself.

Digital markets depend on recommender systems that facilitate the interaction among suppliers, distributors, and consumers; ultimately increasing sales volume and allegedly increasing user utility. Beyond this operational cornerstone, recommender systems also have a passive role on how these markets organize and behave (e.g. funneling consumers into few suppliers or promoting obscure products and services that can better satisfy consumer needs). The potential effect of recommendations appears to be larger on cultural or entertainment and media industries, where product’s uncertainty for consumers and producers is usually high. As such, cultural diversity and market concentration on content platforms (e.g. YouTube, Spotify) are susceptible to the effect of recommendation systems algorithms. The study of diversity has been a focal topic for individual recommendation optimizations, but little attention has been given to aggregated measures of diversity. Previous work on this area states that collaborative based recommender systems have an impact on sales diversity. I expand on this presenting an agent-based model to test the impacts of recommender systems on cultural markets. The model offers a framework to estimate the effects of state-of-the-art content-based and collaborative filtering algorithms on diversity. Early results confirm previous work. Next steps include the use of machine learning algorithms, social influence, and adaptive behavior of users. Current and future work will provide useful insights for marketing modeling, content platform policy, and the use of recommenders in market design.

- by Paolo Garlasco
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- Agent Based Simulation, Netlogo

La vida artificial es una ciencia de frontera que intenta comprender la esencia y la naturaleza de la vida mediante la construcción (simulación o síntesis) de sistemas artificiales que exhiban propiedades normalmente asociadas a los organismos vivos. Se trata, por lo tanto, del primer esfuerzo de investigación sistemático orientado a desentrañar la lógica de la vida -y de los sistemas (artificiales) que exhiben características o comportamientos propios de la vida, entendiendo la vida como un fenómeno de complejidad creciente. Este libro es una introducción a la ciencia de la vida artificial, un tema sobre el que la literatura en español es escasa. En su núcleo, el texto reivindica el papel de la vida artificial como un proyecto de investigación científica por derecho propio y pone de manifiesto su valor científico, filosófico e ingenieril de cara al nuevo marco del conocimiento y a las nuevas formas de acción sobre el mundo que se condensan en las ciencias de la complejidad y en la ingeniería de sistemas complejos, respectivamente.

- by Pawel Sobkowicz
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- Human Factors, Web Mining, Agent Based Simulation, Content Analysis