Describing Agent Societies

Author(s):  
Maksim Tsvetovat

Agent-based approaches provide an invaluable tool for building decentralized, distributed architectures and tying together sets of disparate software tools and architectures. However, while the agents themselves have been gaining complexity, and agent specification languages have been gaining expressive power, little thought has been given to the complexity of agent societies, and languages for describing such societies. In this chapter, I propose a declarative language designed specifically for describing in an expressive way a variety of social interactions. I attempt to avoid the fallacies of artificial restriction, and similarly confounding under-specification of the design domain, yet constructing a rigorous, machine- interpretable semantics. It is my hope that introduction of such semantic will lead to a constructive dialogue between communities of agent-based social modeling and agent-based software design, and lead to a greater integration of agent development toolkits and agent-based modeling toolkits.

2000 ◽  
Vol 03 (01n04) ◽  
pp. 451-461 ◽  
Author(s):  
Eric Bonabeau

Agent-based simulation is a powerful simulation modeling technique that has seen a number of applications in the last five years, including applications to real-world business problems. In this chapter I introduce agent-based simulation and review three applications to business problems: a theme park simulation, a stock market simulation, and a bankwide simulation.


2018 ◽  
Vol 8 (10) ◽  
pp. 1831 ◽  
Author(s):  
İlker Boztepe ◽  
Rıza Erdur

Due to advances in mobile device and wireless networking technologies, it has already been possible to transfer agent technology into mobile computing environments. In this paper, we introduce the Linked Data Aware Agent Development Framework for Mobile Devices (LDAF-M), which is an agent development framework that supports the development of linked data aware agents that run on mobile devices. Linked data, which is the realization of the semantic web vision, refers to a set of best practices for publishing, interconnecting and consuming structured data on the web. An agent developed using LDAF-M has the ability to obtain data from the linked data environment and internalize the gathered data as its beliefs in its belief base. Besides linked data support, LDAF-M has also other prominent features which are its peer-to-peer based communication infrastructure, compliancy with Foundation for Intelligent Physical Agents (FIPA) standards and support for the Belief Desire Intention (BDI) model of agency in mobile device agents. To demonstrate use of LDAF-M, an agent based auction application has been developed as a case study. On the other hand, LDAF-M can be used in any scenario where systems consisting of agents in mobile devices are to be developed. There is a close relationship between agents and linked data, since agents are considered as the autonomous computing entities that will process data in the linked data environment. However, not much work has been conducted on connecting these two related technologies. LDAF-M aims to contribute to the establishment of the connections between agents and the linked data environment by introducing a framework for developing linked data aware agents.


2020 ◽  
Author(s):  
CHIBIN ZHANG ◽  
Paolo Gaudiano

<p>Diversity & Inclusion (D&I) is a topic of increasing relevance across virtually all sectors of our society, with the potential for significant impact on corporations and more broadly on our economy and our society. In spite of the fact that human capital is typically the most valuable asset of every organization, Human Resources (HR) in general and D&I, in particular, are dominated by qualitative approaches. We introduce an agent-based simulation that can quantify the impact of certain aspects of D&I on corporate performance. We show that the simulation provides a parsimonious and compelling explanation of the impact of hiring and promotion biases on the resulting corporate gender balance. We show that varying just two parameters enables us to replicate real-world data about gender imbalances across multiple industry sectors. In addition, we show that the simulation can be used to predict the likely impact of different D&I interventions. Specifically, we show that once a company has become imbalanced, even removing all promotion biases is not sufficient to rectify the situation, and that it can take decades to undo the imbalances initially created by these biases. These and other results demonstrate that agent-based simulation is a powerful approach for managing D&I in corporate settings, and suggest that it has the potential to become an invaluable tool for both strategic and tactical management of human capital. </p>


Author(s):  
V. I. Abramov ◽  
A. N. Kudinov ◽  
D. S. Evdokimov

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.


Author(s):  
Saleh AlZahrani ◽  
Aladdin Ayesh ◽  
Hussein Zedan

Grids are increasingly being used in applications, one of which is e-learning. As most of business and academic institutions (universities) and training centres around the world have adopted this technology in order to create, deliver and manage their learning materials through the Web, the subject has become the focus of investigate. Still, collaboration between these institutions and centres is limited. Existing technologies such as grid, Web services and agents are promising better results. In this article the authors support building our architecture Regionally Distributed Architecture for Dynamic e-Learning Environment (RDADeLE) by combining those technologies via Java Agent DEvelopment Framework (JADE). By describing these agents in details, they prove that agents can be implemented to work well to extend the autonomy and interoperability for learning objects as data grid.


Author(s):  
Marcia R. Friesen ◽  
Richard Gordon ◽  
Robert D. McLeod

In this chapter, the authors examine manifestations of emergence or apparent emergence in agent based social modeling and simulation, and discuss the inherent challenges in building real world models and in defining, recognizing and validating emergence within these systems. The discussion is grounded in examples of research on emergence by others, with extensions from within our research group. The works cited and built upon are explicitly chosen as representative samples of agent-based models that involve social systems, where observation of emergent behavior is a sought-after outcome. The concept of the distinctiveness of social from abiotic emergence in terms of the use of global parameters by agents is introduced.


2020 ◽  
Vol 17 (171) ◽  
pp. 20200396
Author(s):  
Benedikt Kleinmeier ◽  
Gerta Köster ◽  
John Drury

Simulation models of pedestrian dynamics have become an invaluable tool for evacuation planning. Typically, crowds are assumed to stream unidirectionally towards a safe area. Simulated agents avoid collisions through mechanisms that belong to each individual, such as being repelled from each other by imaginary forces. But classic locomotion models fail when collective cooperation is called for, notably when an agent, say a first-aid attendant, needs to forge a path through a densely packed group. We present a controlled experiment to observe what happens when humans pass through a dense static crowd. We formulate and test hypotheses on salient phenomena. We discuss our observations in a psychological framework. We derive a model that incorporates: agents’ perception and cognitive processing of a situation that needs cooperation; selection from a portfolio of behaviours, such as being cooperative; and a suitable action, such as swapping places. Agents’ ability to successfully get through a dense crowd emerges as an effect of the psychological model.


Author(s):  
RAYMOND S. T. LEE

In modern consumer e-shopping environments, customer authentication is a critical process for confirming the identity of the customer. Traditional authentication techniques that rely on the customers to proactively identify themselves (using various schemes) can affect the user-friendliness of the e-shopping experience, and therefore reduce the customers' preference for such facilities. In this paper, we propose an innovative intelligent multiagent-based environment, called iJADE (intelligent Java Agent Development Environment) to provide an intelligent agent-based platform in the e-commerce environment. Contemporary agent development platforms are focused on the autonomy and mobility of the agents, whereas iJADE provides an intelligent layer (known as the "conscious layer") to implement various AI (artificial intelligence) functionalities in order to produce "smart" agents. From an implementation perspective, we introduce an innovative e-shopping authentication scheme called the "iJADE Authenticator", which is an invariant face recognition system that uses intelligent mobile agents. This system can provide fully automatic, mobile and reliable user authentication. More importantly, the authentication process can be carried out without the users necessarily being aware of it. Experimental results are presented for a database of 1020 tested face images obtained under conditions of widely varying facial expressions, viewing perspectives and image sizes. An overall average correct recognition rate of over 90% is attained.


2020 ◽  
Author(s):  
CHIBIN ZHANG ◽  
Paolo Gaudiano

<p>Diversity & Inclusion (D&I) is a topic of increasing relevance across virtually all sectors of our society, with the potential for significant impact on corporations and more broadly on our economy and our society. In spite of the fact that human capital is typically the most valuable asset of every organization, Human Resources (HR) in general and D&I, in particular, are dominated by qualitative approaches. We introduce an agent-based simulation that can quantify the impact of certain aspects of D&I on corporate performance. We show that the simulation provides a parsimonious and compelling explanation of the impact of hiring and promotion biases on the resulting corporate gender balance. We show that varying just two parameters enables us to replicate real-world data about gender imbalances across multiple industry sectors. In addition, we show that the simulation can be used to predict the likely impact of different D&I interventions. Specifically, we show that once a company has become imbalanced, even removing all promotion biases is not sufficient to rectify the situation, and that it can take decades to undo the imbalances initially created by these biases. These and other results demonstrate that agent-based simulation is a powerful approach for managing D&I in corporate settings, and suggest that it has the potential to become an invaluable tool for both strategic and tactical management of human capital. </p>


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