A generic model for representing openness in multi-agent systems

2021 ◽  
Vol 36 ◽  
Author(s):  
Sondes Hattab ◽  
Wided Lejouad Chaari

Abstract Openness is a challenging property that may characterize multi-agent systems (MAS). It refers to their ability to deal with entities leaving and joining agent society over time. This property makes the MAS behaviour complex and difficult to study and analyze, hence the need for a representative model allowing its understanding. In this context, many models were defined in the literature and we propose to classify them into three categories: structural models, functional models and interactional models. The existing models were proposed either for representing structural openness or for modelling functional or interactional ones independently. But, none of them was oriented to represent MAS openness in a global way while considering its three aspects at once. Besides, each one was defined in order to realize a specific objective and in a particular domain of application. In this paper, we propose an evolving KAGR graph. The latter provides a common understanding of openness and unifies its structural, functional and interactional aspects in a generic way. Our model is finally tested and validated on a multi-agent rescue simulator.

2010 ◽  
Vol 2 (1) ◽  
pp. 31-49 ◽  
Author(s):  
Ulf Lotzmann ◽  
Michael Möhring ◽  
Klaus G. Troitzsch

The article discusses the sociological background and the general features of a new simulation toolbox, which was explicitly designed to describe, design and simulate multi-agent systems whose component agents are endowed with the capability to exchange norm invocations and to internalize norms, to develop codes of norms and to change them. This toolbox takes into account that normative behavior can only originate in the interpretation of norm invocations and the deliberate decision to abide by the emerging norms—otherwise what emerges is only a transitory regularity. Agents designed with the help of this toolbox are endowed with initial rule sets that they can vary over time, according to the experience gained.


Author(s):  
Shaheen Fatima ◽  
Michael Wooldridge

This chapter presents an adaptive organizational policy for multi-agent systems called TRACE. TRACE allows a collection of multi-agent organizations to dynamically allocate tasks and resources between themselves in order to efficiently process and incoming stream of tasks. The tasks have deadlines and their arrival pattern changes over time. Hence, at any instant, some organizations could have surplus resources while others could become overloaded. In order to minimize the number of lost requests caused by an overload, the allocation of resources to organizations is changed dynamically by using ideas from microeconomics. We formally show that TRACE has the ability to adapt to load variations, reduce the number of lost requests, and allocate resources to computations on the basis of their criticality. Furthermore, although the solution generated by TRACE is not always Pareto-optimal, TRACE has the properties of feasibility and monotonicity that make it well suited to time-constrained applications. Finally, we present experimental results to demonstrate the performance of TRACE.


Author(s):  
Petros Kefalas ◽  
G. Eleftherakis ◽  
I. Stamatopoulou

Multi-agent systems are highly dynamic since the agents’ abilities and the system configuration often changes over time. In some ways, such multi-agent systems seem to behave like biological processes; new agents appear in the system, some others cease to exist, and communication between agents changes. One of the challenges is to attempt to formally model the dynamic configuration of multi-agent systems. Towards this aim, we present a formal method, namely X-machines, that can be used to formally specify, verify, and test individual agents. In addition, communicating X-machines provide a mechanism for allowing agents to communicate messages to each other. We utilize concepts from biological processes in order to identify and define a set of operations that are able to reconfigure a multi-agent system. In this chapter we present an example in which a biology-inspired system is incrementally built in order to meet our objective.


Author(s):  
Serge V. Chernyshenko

The chapter is devoted to the analysis of possibilities in designing dynamic properties of avatars in multi-agent systems. It is shown that determination of “differential logic” of avatars, based on the use of differential equations, gives sufficient flexibility in describing their behavior over time. At the same time, the differential description usually involves a smooth response of the object to external or internal influences, which for avatars is usually not correct. To eliminate this weak point, it is proposed to use the technology of internal bifurcations, which allows to simulate discontinues effects in the avatar dynamics. It is shown that even when using relatively simple quadratic models of the Lotka-Volterra type, the technique allows to describe rather complex information interactions in the multi-agent systems.


2021 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Hector Roussille ◽  
Önder Gürcan ◽  
Fabien Michel

Blockchain is a very attractive technology since it maintains a public, append-only, immutable and ordered log of transactions which guarantees an auditable ledger accessible by anyone. Blockchain systems are inherently interdisciplinary since they combine various fields such as cryptography, multi-agent systems, distributed systems, social systems, economy, and finance. Furthermore, they have a very active and dynamic ecosystem where new blockchain platforms and algorithms are developed continuously due to the interest of the public and the industries to the technology. Consequently, we anticipate a challenging and interdisciplinary research agenda in blockchain systems, built upon a methodology that strives to capture the rich process resulting from the interplay between the behavior of agents and the dynamic interactions among them. To be effective, however, modeling studies providing insights into blockchain systems, and appropriate description of agents paired with a generic understanding of their components are needed. Such studies will create a more unified field of blockchain systems that advances our understanding and leads to further insight. According to this perspective, in this study, we propose using a generic multi-agent organizational modeling for studying blockchain systems, namely AGR4BS. Concretely, we use the Agent/Group/Role (AGR) organizational modeling approach to identify and represent the generic entities which are common to blockchain systems. We show through four real case studies how this generic model can be used to model different blockchain systems. We also show briefly how it can be used for modeling three well-known attacks on blockchain systems.


Author(s):  
Dino Borri ◽  
Domenico Camarda

Landscapes and townscapes have been studied by many disciplinary areas over time. This study addresses the cognitive and perceptual dimensions of environmental spacescapes in planning by human agents. In fact, because of their dynamic complexity, environmental spacescapes create challengesfor the typical spatial behaviour of an agent perceiving and navigating in it. Therefore, environmental planning activities need to identify and manage the ‘fundamentals’ of spacescapes from the viewpoints of living single agents or multi-agent organizations, those to whom the planning effort is addressed. In this framework, the chapter deals with spatial ontologies in multi-agent systems. Some recent experiments are described and discussed here, highlighting spatial features of navigated environments from an environmental planning perspective.


10.29007/kqfk ◽  
2018 ◽  
Author(s):  
Teddy Bouziat ◽  
Valérie Camps ◽  
Stéphanie Combettes

This paper addresses the modeling and design of Systems of Systems (SoS) as well as inter multi-agent systems cooperation. It presents and illustrates a new generic model to describe formally SoS. Then, this model is used to propose a study of inter-AMAS (Adaptive Multi-Agent System) cooperation. Each AMAS, reified as a component-system of a SoS, uses a cooperative decision process in order to interact with other AMAS and to collectively give rise to a relevant overall function at the SoS level. The proposed model as well as the inter-AMAS study are instantiated to a simulated resources transportation problem.


2004 ◽  
Vol 13 (01) ◽  
pp. 115-139 ◽  
Author(s):  
ARTUR S. d'AVILA GARCEZ ◽  
LUÍS C. LAMB ◽  
KRYSIA BRODA ◽  
DOV M. GABBAY

Neural-Symbolic Systems concern the integration of the symbolic and connectionist paradigms of Artificial Intelligence. Distributed knowledge representation is traditionally seen under a symbolic perspective. In this paper, we show how neural networks can represent distributed symbolic knowledge, acting as multi-agent systems with learning capability (a key feature of neural networks). We apply the framework of Connectionist Modal Logics to well-known testbeds for distributed knowledge representation formalisms, namely the muddy children and the wise men puzzles. Finally, we sketch a full solution to these problems by extending our approach to deal with knowledge evolution over time.


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