Multi-agent System Organization Research Articles

A new hierarchical multi group particle swarm optimization with different task allocations inspired by holonic multi agent systems

Nowadays expert systems have been used in different fields. They must be able to operate as quickly and efficiently as possible. So, they need optimization mechanism in their different parts and optimization is a critical part of almost all expert systems. Because of difficulties in real world problems, traditional optimization techniques commonly cannot solve them. Therefore, stochastic algorithms are used to do the optimization in expert systems. Particle swarm optimization (PSO) is one the most famous stochastic optimization algorithms. But this algorithm has some difficulties like losing diversity, premature convergence, trapping in local optimums and imbalance between exploration and exploitation. To overcome these drawbacks, inspired by holonic organization in multi agent systems, a new hierarchical multi group structure for PSO is presented in this paper. Considering the particles in PSO as simple agents, PSO is a kind of multi agent system. Existence of different facilities and organizations in multi agent systems and their great impact on performance encouraged us to use them. So, inspired by holonic multi agent systems, a new structure for PSO is presented. This work has been done for the first time in the literature. Meanwhile, to promote exploration and exploitation ability of proposed structure and create a suitable balance between them, different tasks are assigned to different groups of this structure. So, a holonic PSO with different task allocations (HPSO-DTA) is created. It provides the opportunity to employ all aspects for empowering PSO including parameter settings, neighborhood topologies and learning strategies to enhance the ability of it unlike other versions of PSO that use only one of these aspects to improve their solutions. This structure provides a lot of advantages for PSO. It is a new topological structure that improves the performance of PSO. It provides several leaders with efficient information to guide the particles in the search space. Also, it helps to control suitable information flow between groups and particles in order to preserve diversity and prevent from trapping in local optimums. Meanwhile, with assigning different tasks to different groups of proposed structure, an appropriate balance between exploration and exploitation is created to enhance the performance of the algorithm. In each group, based on its assigned task, particles use different parameters settings, different dynamic neighborhood topologies and different learning strategies which are proposed in this paper to enhance the performance of algorithm. A set of thirty four benchmark functions are used to evaluate the performance of proposed structure. Proposed algorithm is compared with a set of well-known PSO algorithms that their efficiency have been proved. Experimental results and comparative analysis demonstrate good performance of HPSO-DTA compared to other algorithms. Its solution accuracy, convergence speed and robustness is completely appropriate especially in more complicated benchmarks.

Computational Accountability in MAS Organizations with ADOPT

This work studies how the notion of accountability can play a key role in the design and realization of distributed systems that are open and that involve autonomous agents that should harmonize their own goals with the organizational goals. The socio–technical systems that support the work inside human companies and organizations are examples of such systems. The approach that is proposed in order to pursue this purpose is set in the context of multiagent systems organizations, and relies on an explicit specification of relationships among the involved agents for capturing who is accountable to whom and for what. Such accountability relationships are created along with the agents’ operations and interactions in a shared environment. In order to guarantee accountability as a design property of the system, a specific interaction protocol is suggested. Properties of this protocol are verified, and a case study is provided consisting of an actual implementation. Finally, we discuss the impact on real-world application domains and trace possible evolutions of the proposal.

Formal modeling towards a dynamic organization of multi-agent systems using communicating X-machine and Z-notation

Formal modeling towards a dynamic organization of multi-agent systems using communicating X-machine and Z-notation

Adaptive organizational changes in agent-oriented methodologies

AbstractWe analyze the problem of modeling and developing multiagent systems (MASs) from the organizational theory point of view. In particular, we focus on the critical issue of adapting MASs organizations whenever changes in the structure of the MAS are required. We survey different relevant agent-oriented methodologies and discuss their suitability in dealing with adaptation in multiagent organizations. Finally, we present some critical considerations about the analyzed methodologies together with some open issues related to the process of modeling organizations for facilitating their adaptations.

The MACODO organization model for context-driven dynamic agent organizations

Today's distributed applications such as sensor networks, mobile multimedia applications, and intelligent transportation systems pose huge engineering challenges. Such systems often comprise different components that interact with each other as peers, as such forming a decentralized system. The system components and collaborations change over time, often in unanticipated ways. Multiagent systems belong to a class of decentralized systems that are known for realizing qualities such as adaptability, robustness, and scalability in such environments. A typical way to structure and manage interactions among agents is by means of organizations. Existing approaches usually endow agents with a dual responsibility: on the one hand agents have to play roles providing the associated functionality in the organization, on the other hand agents are responsible for setting up organizations and managing organization dynamics. Engineering realistic multiagent systems in which agents encapsulate this dual responsibility is a complex task. In this article, we present an organization model for context-driven dynamic agent organizations. The model defines abstractions that support application developers to describe dynamic organizations. The organization model is part of an integrated approach, called MACODO: Middleware Architecture for COntext-driven Dynamic agent Organizations. The complementary part of the MACODO approach is a middleware platform that supports the distributed execution of dynamic organizations specified using the abstractions, as described in Weyns et al. [2009]. In the model, the life-cycle management of dynamic organizations is separated from the agents: organizations are first-class citizens, and their dynamics are governed by laws. The laws specify how changes in the system (e.g., an agent joins an organization) and changes in the context (e.g., information observed in the environment) lead to dynamic reorganizations. As such, the model makes it easier to understand and specify dynamic organizations in multiagent systems, and promotes reusing the life-cycle management of dynamic organizations. The organization model is formally described to specify the semantics of the abstractions, and ensure its type safety. We apply the organization model to specify dynamic organizations for a traffic monitoring application.

The MACODO middleware for context-driven dynamic agent organizations

One of the major challenges in engineering distributed multiagent systems is the coordination necessary to align the behavior of different agents. Decentralization of control implies a style of coordination in which the agents cooperate as peers with respect to each other and no agent has global control over the system, or global knowledge about the system. The dynamic interactions and collaborations among agents are usually structured and managed by means of roles and organizations. In existing approaches agents typically have a dual responsibility: on the one hand playing roles within the organization, on the other hand managing the life-cycle of the organization itself, for example, setting up the organization and managing organization dynamics. Engineering realistic multiagent systems in which agents encapsulate this dual responsibility is a complex task. In this article, we present a middleware for context-driven dynamic agent organizations. The middleware is part of an integrated approach, called MACODO: Middleware Architecture for COntext-driven Dynamic agent Organizations. The complementary part of the MACODO approach is an organization model that defines abstractions to support application developers in describing dynamic organizations, as described in Weyns et al. [2010]. The MACODO middleware offers the life-cycle management of dynamic organizations as a reusable service separated from the agents, which makes it easier to understand, design, and manage dynamic organizations in multiagent systems. We give a detailed description of the software architecture of the MADOCO middleware. The software architecture describes the essential building blocks of a distributed middleware platform that supports the MACODO organization model. We used the middleware architecture to develop a prototype middleware platform for a traffic monitoring application. We evaluate the MACODO middeware architecture by assessing the adaptability, scalability, and robustness of the prototype platform.

Systems of exchange values as tools for multi-agent organizations

This paper introduces systems of exchange values as tools for the organization of multi-agent systems. Systems of exchange values are defined on the basis of the theory of social exchanges, developed by Piaget and Homans. A model of social organization is proposed, where social relations are construed as social exchanges and exchange values are put into use in the support of the continuity of the performance of social exchanges. The dynamics of social organizations is formulated in terms of the regulation of exchanges of values, so that social equilibrium is connected to the continuity of the interactions. The concept of supervisor of social equilibrium is introduced as a centralized mechanism for solving the problem of the equilibrium of the organization The equilibrium supervisor solves such problem making use of a qualitative Markov Decision Process that uses numerical intervals for the representation of exchange values.

Systems of exchange values as tools for multi-agent organizations

Abstract This paper introduces systems of exchange values as tools for the organization of multi-agent systems. Systems of exchange values are defined on the basis of the theory of social exchanges, developed by Piaget and Homans. A model of social organization is proposed, where social relations are construed as social exchanges and exchange values are put into use in the support of the continuity of the performance of social exchanges. The dynamics of social organizations is formulated in terms of the regulation of exchanges of values, so that social equilibrium is connected to the continuity of the interactions. The concept of supervisor of social equilibrium is introduced as a centralized mechanism for solving the problem of the equilibrium of the organization The equilibrium supervisor solves such problem making use of a qualitative Markov Decision Process that uses numerical intervals for the representation of exchange values.