Analysis and verification of multi-agent interaction protocols

1999 ◽  
Author(s):  
Wu Wen ◽  
Fumio Mizoguchi
Keyword(s):  
Interaction Protocols ◽  
Agent Interaction ◽  
Multi Agent

A GENERIC FORMAL FRAMEWORK FOR CONSTRUCTING AGENT INTERACTION PROTOCOLS

2005 ◽  
Vol 15 (01) ◽  
pp. 61-85 ◽  
Author(s):  
BO CHEN ◽  
SAMIRA SADAOUI
Keyword(s):  
Online Auction ◽  
Multi Agent Systems ◽  
Interaction Protocols ◽  
Formal Framework ◽  
Agent Interaction ◽  
Finite State ◽  
Generic Agent ◽  
Multi Agent ◽  
Almost All ◽  
Abstraction Levels

Agent interaction protocols (AIP) design is one of the principal issues for building multi-agent systems. Indeed, the construction of AIP should integrate theories, methodologies and tools. We propose in this paper a unifying framework that provides a generic agent architecture to be reused as well as a methodology to construct and refine AIP specifications in an incremental way. This framework is based on the highly expressive formal language Lotos and its related technologies, such as finite state machines and temporal logics. Hence, the proposed framework also facilitates formal validation and verification of AIP specifications using rigorous tools. We argue that there are three layers of semantics of Lotos specifications that can improve Lotos expressivity in describing agent interaction. Therefore, this framework can describe almost all aspects of agent interaction and at different abstraction levels. In addition, we demonstrate how to generate an online auction protocol from the generic framework, and how to validate and verify this protocol.

Coordinating Agent Interactions Under Open Environments

2011 ◽  
pp. 1430-1443
Author(s):  
Quan Bai ◽  
Minjie Zhang
Keyword(s):  
Multi Agent Systems ◽  
Social Ability ◽  
Agent Interactions ◽  
Interaction Protocols ◽  
The Social ◽  
Open Environments ◽  
Agent Interaction ◽  
Coloured Petri Net ◽  
Multi Agent ◽  
Rich Interaction

An intelligent agent is a reactive, proactive, autonomous, and social entity. The social ability of an agent is exercised in a multi-agent system (MAS), which constitutes a collection of such agents. Current multi-agent systems mostly work in complex, open, and dynamic environments. In an open environment, many facts, such as domain constraints, agent number, and agent relationships, are not fixed. That brings a lot of difficulties to coordinate agents’ interactions and cooperation. One major problem that impedes agent interaction is that most current agent interaction protocols are not very suitable for open environments. In this chapter, we introduce an approach to ameliorate agent interactions from two perspectives. First, the approach can enable agents to form knowledge “rich” interaction protocols by using ontologies. Second, we use coloured Petri net (CPN) based methods to enable agents to form interaction protocols dynamically, which are more suitable for agent interaction under open environments.

Coordinating Agent Interactions Under Open Environments

2006 ◽  
pp. 52-67 ◽  
Author(s):  
Quan Bai ◽  
Minjie Zhang
Keyword(s):  
Multi Agent Systems ◽  
Social Ability ◽  
Agent Interactions ◽  
Interaction Protocols ◽  
The Social ◽  
Open Environments ◽  
Agent Interaction ◽  
Coloured Petri Net ◽  
Multi Agent ◽  
Rich Interaction

An intelligent agent is a reactive, proactive, autonomous, and social entity. The social ability of an agent is exercised in a multi-agent system (MAS), which constitutes a collection of such agents. Current multi-agent systems mostly work in complex, open, and dynamic environments. In an open environment, many facts, such as domain constraints, agent number, and agent relationships, are not fixed. That brings a lot of difficulties to coordinate agents’ interactions and cooperation. One major problem that impedes agent interaction is that most current agent interaction protocols are not very suitable for open environments. In this chapter, we introduce an approach to ameliorate agent interactions from two perspectives. First, the approach can enable agents to form knowledge “rich” interaction protocols by using ontologies. Second, we use coloured Petri net (CPN) based methods to enable agents to form interaction protocols dynamically, which are more suitable for agent interaction under open environments.

UUV formation system modeling and simulation research based on Multi-Agent Interaction Chain

2015 ◽  
Vol 06 (02) ◽  
pp. 1550019 ◽  
Author(s):  
Hongtao Liang ◽  
Fengju Kang ◽  
Honghong Li
Keyword(s):  
Modeling And Simulation ◽  
System Modeling ◽  
Rule Base ◽  
Communication Model ◽  
Static Structure ◽  
Dynamic Contract ◽  
Novel Approach ◽  
Agent Interaction ◽  
Multi Agent ◽  
Formation System

Unmanned Underwater Vehicle (UUV) formation system has an important role in the utilization of marine resource. In order to provide an efficient method to research modeling and simulation of UUV formation in the marine environment, the novel approach based on Multi-Agent Interaction Chain was proposed for the UUV formation system. Firstly, Multi-Agent Interaction Chain was analyzed, which mainly considered task and role of UUV in the formation, and the overall modeling process of UUV formation system based on Multi-Agent Interaction Chain was established. Then, the static structure of Multi-Agent Interaction Chain was researched focusing on Hybrid UUV-Agent model structure from the UUV-Agent State-Set and UUV-Agent Rule-Base which were the two aspects to strengthen reliability of interaction chain; the dynamic mechanism of Multi-Agent Interaction Chain was designed, which was focused on collaboration model and communication model through the Adaptive Dynamic Contract Net Protocol and KQML/XML/RTI. Finally, three experiments were established to verify the validity and effectiveness of proposed modeling approach for UUV formation system. Simulation results show the proposed model has good performance, which has important theoretical innovation and application prospects.

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