Economic coordination mechanisms for holonic multi-agent systems

2002 ◽  
Author(s):  
H.H. Adelsberger
Keyword(s):  
Coordination Mechanisms ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Aspects of Openness in Multi-Agent Systems

2011 ◽  
pp. 119-131 ◽  
Author(s):  
Marcos De Oliveira ◽  
Martin Purvis
Keyword(s):  
Autonomous Agents ◽  
Institutional Environment ◽  
Coordination Mechanisms ◽  
Coloured Petri Nets ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Agent Societies ◽  
Agent Interactions ◽  
Complex Agent ◽  
Multi Agent

In the distributed multi-agent systems discussed in this chapter, heterogeneous autonomous agents interoperate in order to achieve their goals. In such environments, agents can be embedded in diverse contexts and interact with agents of various types and behaviours. Mechanisms are needed for coordinating these multi-agent interactions, and so far they have included tools for the support of conversation protocols and tools for the establishment and management of agent groups and electronic institutions. In this chapter, we explore the necessity of dealing with openness in multi-agent systems and its relation with the agent’s autonomy. We stress the importance to build coordination mechanisms capable of managing complex agent societies composed by autonomous agents and introduce our institutional environment approach, which includes the use of commitments and normative spaces. It is based on a metaphor in which agents may join an open system at any time, but they must obey regulations in order to maintain a suitable reputation, that reflects its degree of cooperation with other agents in the group, and make them a more desired partner for others. Coloured Petri Nets are used to formalize a workflow in the institutional environment defining a normative space that guides the agents during interactions in the conversation space.

EFFICIENCY, INCENTIVES, AND COMPUTATIONAL TRACTABILITY IN MAS-COORDINATION

1999 ◽  
Vol 08 (01) ◽  
pp. 1-14 ◽  
Author(s):  
PETER GOMBER ◽  
CLAUDIA SCHMIDT ◽  
CHRISTOF WEINHARDT
Keyword(s):  
Operational Planning ◽  
Coordination Mechanisms ◽  
Business Planning ◽  
Efficient Allocation ◽  
Multi Agent Systems ◽  
Trade Off ◽  
Agent Systems ◽  
Common Basis ◽  
Multi Agent ◽  
Planning Problems

This paper focuses on market-like coordination mechanisms in multi-agent systems, with applications to business planning. Several fundamental criteria are derived in order to evaluate market-like coordination mechanisms. The central criterion is the efficient allocation of jobs to agents. Assuming a relationship between classes of operational planning problems and certain coordination mechanisms, business planning problems are classified on the basis of their relevant attributes. Coordination mechanisms for each of the classes are then introduced on the basis of auction theory and investigated with respect to the trade-off between efficiency and computational tractability. All of the mechanisms prove to have a common basis: the Vickrey Auction.

scholarly journals Collective Learning in Multi-Agent Systems Based on Cultural Algorithms

2014 ◽  
Vol 17 (2) ◽  
Author(s):  
Juan Terán ◽  
José L. Aguilar ◽  
Mariela Cerrada
Keyword(s):  
Learning Model ◽  
Collective Learning ◽  
Coordination Mechanisms ◽  
Cultural Algorithms ◽  
Interaction Patterns ◽  
Multi Agent Systems ◽  
Computational Tool ◽  
Industrial Automation ◽  
Agent Systems ◽  
Multi Agent

This paper aims to present a learning model for coordination schemes in Multi-Agent Systems (MAS) based on Cultural Algorithms (CA). In this model, the individuals (one of the CA components) are the different conversations that may occur in any multi-agent systems, and the coordination scheme learned is at the level of the way to perform the communication protocols into the conversation. A conversation can has sub-conversations, and the sub-conversations and/or conversations are identified with a particular type of conversation associated with a certain interaction patterns. The interaction patterns use the coordination mechanisms existing in the literature. In order to simulate the proposed learning model, we develop a computational tool called CLEMAS, which has been used to apply the model to a case of study in industrial automation, related to a Faults Management System based on Agents.

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