scholarly journals Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential

2019 ◽  
Vol 81 (3) ◽  
pp. 339-359
Author(s):  
V. I. Abramov ◽  
A. N. Kudinov ◽  
D. S. Evdokimov
Keyword(s):  
Social Sciences ◽  
Fine Tuning ◽  
Technical Development ◽  
Macro Level ◽  
Multi Agent Systems ◽  
Social Modeling ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
Innovative Potential

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.

Analysis and synthesis: multi-agent systems in the social sciences

2012 ◽  
Vol 27 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Robert E. Marks
Keyword(s):  
Social Sciences ◽  
Computer Science ◽  
Common Source ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Social ◽  
Analysis And Synthesis ◽  
Multi Agent ◽  
Computational Systems

AbstractAlthough they flow from a common source, the uses of multi-agent systems (or ‘agent-based computational systems’––ACE) vary between the social sciences and computer science. The distinction can be broadly summarized as analysis versus synthesis, or explanation versus design. I compare and contrast these uses, and discuss sufficiency and necessity in simulations in general and in multi-agent systems in particular, with a computer science audience in mind.

scholarly journals Use of the Multi-Agent Paradigm in Sustainable Tourism

2018 ◽  
Vol 7 (1) ◽  
pp. 5-24 ◽  
Author(s):  
Martina Husáková
Keyword(s):  
Complex Systems ◽  
Sustainable Tourism ◽  
Multi Agent Systems ◽  
Economic Prosperity ◽  
Cultural Economic ◽  
Bottom Up ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
In Silico Models

Abstract Complex systems are characterised by a huge amount of components, which are highly linked with each other. Tourism is one of the examples of complex systems collecting various activities leading to the enrichment of travellers in the view of receiving new experiences and increasing economic prosperity of specific destinations. The complex systems can be investigated with various bottom-up and top-down approaches. The multi-agent-based modelling is the bottom-up approach that is focused on the representation of individual entities for the exploration of possible interactions among them and their effects on surrounding environments. These systems are able to integrate knowledge of socio-cultural, economic, physical, biological or environmental systems for in-silico models development, which can be used for experimentation with a system. The main aim of the presented text is to introduce links between tourism, complexity and to advocate usefulness of the multi-agent-based systems for the exploration of tourism and its sustainability. The evaluation of suitability of the multi-agent systems in tourism is based on the investigation of fundamental characteristics of these two systems and on the review of specific applications of the multi-agent systems in sustainable tourism.

scholarly journals Trust in multi-agent systems

2004 ◽  
Vol 19 (1) ◽  
pp. 1-25 ◽  
Author(s):  
SARVAPALI D. RAMCHURN ◽  
DONG HUYNH ◽  
NICHOLAS R. JENNINGS
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Comprehensive Treatment ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Core ◽  
Open Distributed Systems ◽  
Multi Agent

Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular, we survey the state of the art and provide an account of the main directions along which research efforts are being focused. In so doing, we critically evaluate the relative strengths and weaknesses of the main models that have been proposed and show how, fundamentally, they all seek to minimise the uncertainty in interactions. Finally, we outline the areas that require further research in order to develop a comprehensive treatment of trust in complex computational settings.

Enhancing Social Networks with Agent and Semantic Web Technologies

2012 ◽  
pp. 83-100 ◽  
Author(s):  
Federico Bergenti ◽  
Enrico Franchi ◽  
Agostino Poggi
Keyword(s):  
Social Networks ◽  
Semantic Web ◽  
Collaborative Work ◽  
Multi Agent Systems ◽  
Semantic Web Technologies ◽  
Agent Based ◽  
Web Technologies ◽  
Agent Systems ◽  
Multi Agent ◽  
Relevant Work

In this chapter, the authors describe the relationships between multi-agent systems, social networks, and the Semantic Web within collaborative work; they also review how the integration of multi-agent systems and Semantic Web technologies and techniques can be used to enhance social networks at all scales. The chapter first provides a review of relevant work on the application of agent-based models and abstractions to the key ingredients of our work: collaborative systems, the Semantic Web, and social networks. Then, the chapter discusses the reasons current multi-agent systems and their foreseen evolution might be a fundamental means for the realization of the future Semantic Social Networks. Finally, some conclusions are drawn.

Agent-Based Software Engineering, Paradigm Shift, or Research Program Evolution

2018 ◽  
pp. 284-296
Author(s):  
Yves Wautelet ◽  
Christophe Schinckus ◽  
Manuel Kolp
Keyword(s):  
Organizational Context ◽  
Project Managers ◽  
Flexible Systems ◽  
Multi Agent Systems ◽  
Modeling Tools ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
Agent Orientation ◽  
Development Agendas

Information systems are deeply linked to human activities. Unfortunately, development methodologies have been traditionally inspired by programming concepts and not by organizational and human ones. This leads to ontological and semantic gaps between the systems and their environments. The adoption of agent orientation and multi-agent systems (MAS) helps to reduce these gaps by offering modeling tools based on organizational concepts (actors, agents, goals, objectives, responsibilities, social dependencies, etc.) as fundamentals to conceive systems through all the development process. Moreover, software development is becoming increasingly complex. Stakeholders' expectations are growing higher while the development agendas have to be as short as possible. Project managers, business analysts, and software developers need adequate processes and models to specify the organizational context, capture requirements, and build efficient and flexible systems.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 118-136 ◽  
Author(s):  
Robert E. Smith ◽  
Claudio Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

Trust-Aware Recommender Systems for Open and Mobile Virtual Communities

2010 ◽  
pp. 326-345
Author(s):  
N. Sahli ◽  
G. Lenzini
Keyword(s):  
Recommender Systems ◽  
Virtual Communities ◽  
Multi Agent Systems ◽  
Artificial Intelligent ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent

This chapter surveys and discusses relevant works in the intersection among trust, recommendations systems, virtual communities, and agent-based systems. The target of the chapter is showing how, thanks to the use of trust-based solutions and artificial intelligent solutions like that understanding agents-based systems, the traditional recommender systems can improve the quality of their predictions. Moreover, when implemented as open multi-agent systems, trust-based recommender systems can efficiently support users of mobile virtual communities in searching for places, information, and items of interest.

Rule Engines and Agent-Based Systems

2012 ◽  
pp. 211-218 ◽  
Author(s):  
Agostino Poggi ◽  
Michele Tomaiuolo
Keyword(s):  
Dynamic Environments ◽  
Multi Agent Systems ◽  
Rule Engine ◽  
Rule Based ◽  
Agent Based ◽  
Agent Systems ◽  
Loosely Coupled ◽  
Domain Specific ◽  
Multi Agent ◽  
Good Support

Expert systems are successfully applied to a number of domains. Often built on generic rule-based systems, they can also exploit optimized algorithms. On the other side, being based on loosely coupled components and peer to peer infrastructures for asynchronous messaging, multi-agent systems allow code mobility, adaptability, easy of deployment and reconfiguration, thus fitting distributed and dynamic environments. Also, they have good support for domain specific ontologies, an important feature when modelling human experts’ knowledge. The possibility of obtaining the best features of both technologies is concretely demonstrated by the integration of JBoss Rules, a rule engine efficiently implementing the Rete-OO algorithm, into JADE, a FIPA-compliant multi-agent system.

Attack of the Rainbow Bots

2011 ◽  
pp. 8-43
Author(s):  
Samuel G. Collins ◽  
Goran P. Trajkovski
Keyword(s):  
Social Sciences ◽  
Cultural Studies ◽  
Software Agent ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
It Education ◽  
Multi Agent ◽  
Humanities And Social Sciences ◽  
Lost In Translation

Many in IT education—following on more than twenty years of multicultural critique and theory—have integrated “diversity” into their curricula. But while this is certainly laudable, there is an irony to the course “multiculturalism” has taken in the sciences in general. By submitting to a canon originating in the humanities and social sciences—no matter how progressive or well-intentioned—much of the transgressive and revolutionary character of multicultural pedagogies is lost in translation, and the insights of radical theorists become, simply, one more module to graft onto existing curricula or, at the very least, another source of authority joining or supplanting existing canons. In this essay, we feel that introducing diversity into IT means generating this body of creative critique from within IT itself, in the same way multiculturalism originated in the critical, transgressive spaces between literature, cultural studies, anthropology and pedagogy. The following traces our efforts to develop isomorphic critiques from recent insights into multi-agent systems using a JAVA-based, software agent we’ve developed called “Izbushka.”

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