scholarly journals PLAMAGS: a Unified Framework and Language for Efficient Multi-Agent Geo-Simulation Development

10.5772/10022 ◽  
2010 ◽  
Author(s):  
Tony Garneau ◽  
Bernard Moulin ◽  
Sylvain Delisle
Keyword(s):  
Unified Framework ◽  
Multi Agent

scholarly journals A Unified Framework Design for Finite-Time Bipartite Consensus of Multi-Agent Systems

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Jiaju Yu ◽  
Jiashang Yu ◽  
Pengfei Zhang ◽  
TingTing Yang ◽  
Xiurong Chen
Keyword(s):  
Finite Time ◽  
Multi Agent Systems ◽  
Unified Framework ◽  
Agent Systems ◽  
Framework Design ◽  
Multi Agent ◽  
Bipartite Consensus

scholarly journals A HYBRID MODEL FOR SHARING INFORMATION BETWEEN FUZZY, UNCERTAIN AND DEFAULT REASONING MODELS IN MULTI-AGENT SYSTEMS

2002 ◽  
Vol 10 (04) ◽  
pp. 401-450 ◽  
Author(s):  
XUDONG LUO ◽  
CHENGQI ZHANG ◽  
NICHOLAS R. JENNINGS
Keyword(s):  
Hybrid Model ◽  
Approximate Reasoning ◽  
Default Reasoning ◽  
Uncertain Reasoning ◽  
Uncertain Information ◽  
Multi Agent Systems ◽  
Unified Framework ◽  
Agent Systems ◽  
Special Cases ◽  
Multi Agent

This paper develops a hybrid model which provides a unified framework for the following four kinds of reasoning: 1) Zadeh's fuzzy approximate reasoning; 2) truth-qualification uncertain reasoning with respect to fuzzy propositions; 3) fuzzy default reasoning (proposed, in this paper, as an extension of Reiter's default reasoning); and 4) truth-qualification uncertain default reasoning associated with fuzzy statements (developed in this paper to enrich fuzzy default reasoning with uncertain information). Our hybrid model has the following characteristics: 1) basic uncertainty is estimated in terms of words or phrases in natural language and basic propositions are fuzzy; 2) uncertainty, linguistically expressed, can be handled in default reasoning; and 3) the four kinds of reasoning models mentioned above and their combination models will be the special cases of our hybrid model. Moreover, our model allows the reasoning to be performed in the case in which the information is fuzzy, uncertain and partial. More importantly, the problems of sharing the information among heterogeneous fuzzy, uncertain and default reasoning models can be solved efficiently by using our model. Given this, our framework can be used as a basis for information sharing and exchange in knowledge-based multi-agent systems for practical applications such as automated group negotiations. Actually, to build such a foundation is the motivation of this paper.

scholarly journals Edge-Event-Triggered Synchronization for Multi-Agent Systems with Nonlinear Controller Outputs

2020 ◽  
Vol 10 (15) ◽  
pp. 5250
Author(s):  
Jie Liu ◽  
Ming-Zhe Dai ◽  
Chengxi Zhang ◽  
Jin Wu
Keyword(s):  
Communication Networks ◽  
Data Transmission ◽  
Policy Design ◽  
Multi Agent Systems ◽  
Nonlinear Controller ◽  
Unified Framework ◽  
Nonlinear Characteristics ◽  
Agent Systems ◽  
Multi Agent ◽  
Event Triggered

This paper addresses the synchronization problem of multi-agent systems with nonlinear controller outputs via event-triggered control, in which the combined edge state information is utilized, and all controller outputs are nonlinear to describe their inherent nonlinear characteristics and the effects of data transmission in digital communication networks. First, an edge-event-triggered policy is proposed to implement intermittent controller updates without Zeno behavior. Then, an edge-self-triggered solution is further investigated to achieve discontinuous monitoring of sensors. Compared with the previous event-triggered mechanisms, our policy design considers the controller output nonlinearities. Furthermore, the system’s inherent nonlinear characteristics and networked data transmission effects are combined in a unified framework. Numerical simulations demonstrate the effectiveness of our theoretical results.

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