A Framework for Dynamic Agent Organizations

2009 ◽  
pp. 446-459 ◽  
Author(s):  
Shaheen Fatima ◽  
Michael Wooldridge
Keyword(s):  
Pareto Optimal ◽  
Trace Trace ◽  
Multi Agent Systems ◽  
Load Variations ◽  
Agent Systems ◽  
Incoming Stream ◽  
Multi Agent ◽  
Changes Over Time ◽  
Arrival Pattern ◽  
Over Time

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.

Formal Modelling of the Dynamic Behaviour of Biology-Inspired, Agent-Based Systems

2011 ◽  
pp. 243-276 ◽  
Author(s):  
Petros Kefalas ◽  
G. Eleftherakis ◽  
I. Stamatopoulou
Keyword(s):  
Formal Method ◽  
Biological Processes ◽  
Multi Agent Systems ◽  
Dynamic Configuration ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
Changes Over Time ◽  
Test Individual ◽  
Over Time

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.

Approach for Negotiation Problems in Multi-Agent Systems for DC Micro Grid Using Multi-Objective Evolutionary Algorithms

2015 ◽  
Vol 713-715 ◽  
pp. 2106-2109
Author(s):  
Mauricio Mauledoux ◽  
Edilberto Mejía-Ruda ◽  
Oscar I. Caldas
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Algorithms ◽  
Pareto Optimal ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Objective ◽  
Multi Agent ◽  
Micro Grid ◽  
Optimal Space ◽  
Multi Agents

The work is devoted to solve allocation task problem in multi agents systems using multi-objective genetic algorithms and comparing the technique with methods used in game theories. The paper shows the main advantages of genetic algorithms and the way to apply a parallel approach dividing the population in sub-populations saving time in the search and expanding the coverage of the solution in the Pareto optimal space.

Simulating Normative Agents

2010 ◽  
Vol 2 (1) ◽  
pp. 31-49 ◽  
Author(s):  
Ulf Lotzmann ◽  
Michael Möhring ◽  
Klaus G. Troitzsch
Keyword(s):  
Multi Agent Systems ◽  
Normative Behavior ◽  
Agent Systems ◽  
Rule Sets ◽  
Normative Agents ◽  
Multi Agent ◽  
Over Time

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.

Design of Avatars With “Differential” Logic

2020 ◽  
pp. 121-131
Author(s):  
Serge V. Chernyshenko
Keyword(s):  
Differential Equations ◽  
Dynamic Properties ◽  
Multi Agent Systems ◽  
Weak Point ◽  
Agent Systems ◽  
Complex Information ◽  
Multi Agent ◽  
Quadratic Models ◽  
Over Time

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.

A generic model for representing openness in multi-agent systems

2021 ◽  
Vol 36 ◽  
Author(s):  
Sondes Hattab ◽  
Wided Lejouad Chaari
Keyword(s):  
Structural Models ◽  
Generic Model ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Specific Objective ◽  
Functional Models ◽  
Representative Model ◽  
Multi Agent ◽  
Common Understanding ◽  
Over Time

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.

Spatial Ontologies in Multi-Agent Environmental Planning

2011 ◽  
pp. 272-295 ◽  
Author(s):  
Dino Borri ◽  
Domenico Camarda
Keyword(s):  
Environmental Planning ◽  
Spatial Behaviour ◽  
Multi Agent Systems ◽  
Dynamic Complexity ◽  
Agent Systems ◽  
Spatial Features ◽  
Planning Effort ◽  
Multi Agent ◽  
Over Time ◽  
Living Single

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.

APPLYING CONNECTIONIST MODAL LOGICS TO DISTRIBUTED KNOWLEDGE REPRESENTATION PROBLEMS

2004 ◽  
Vol 13 (01) ◽  
pp. 115-139 ◽  
Author(s):  
ARTUR S. d'AVILA GARCEZ ◽  
LUÍS C. LAMB ◽  
KRYSIA BRODA ◽  
DOV M. GABBAY
Keyword(s):  
Neural Networks ◽  
Knowledge Representation ◽  
Modal Logics ◽  
Multi Agent Systems ◽  
Distributed Knowledge ◽  
Learning Capability ◽  
Agent Systems ◽  
Multi Agent ◽  
Full Solution ◽  
Over Time

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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