Results (8)
Search Parameters:
Keyword: Multi-Agent Systems
Towards Process Standardization for Requirements Analysis of Agent-Based Systems
The development of agent-based systems is negatively impacted by the lack of process standardization across the major development phases, such as the requirements analysis phase. This issue creates a key barrier for agent technology stockholders regarding comprehending and analyzing complexity associated with these systems specifications. Instead, such fundamental low-level infrastructure is loosely attended to in…
Read More Revealing Strengths, Weaknesses and Prospects of Intelligent Collaborative e-Learning Systems
The rapid evolution of Collaborative e-Learning Systems migrates to the use of new technologies such the artificial intelligence (AI). In this context, the role of AI in increasing the quality of learning and making it more productive, persistent and efficient. In addition, it can accomplish repetitive and complex tasks in record time and unmatched accuracy.…
Read More Comparative Study of Adaptive Consensus Control of Euler-Lagrange Systems on Directed Network Graph
A comparative study between adaptive consensus control of multi-agent systems composed of fully actuated mobile robots which are described as a class of Euler-Lagrange systems on directed network graphs based on the notion of inverse optimal H∞ control criterion (Controller I), and the similar control strategy without H∞ control criterion (Controller II), is given in this paper.…
Read More Modeling Control Agents in Social Media Networks Using Reinforcement Learning
Designing efficient control strategies for opinion dynamics is a challenging task. Understanding how individuals change their opinions in social networks is essential to countering malicious actors and fake news and mitigating their effect on the network. In many applications such as marketing design, product launches, etc., corporations often post curated news or feeds on social…
Read More A New Technique to Accelerate the Learning Process in Agents based on Reinforcement Learning
The use of decentralized reinforcement learning (RL) in the context of multi-agent systems (MAS) poses some difficult problems. The speed of the learning process for example. Indeed, if the convergence of these algorithms has been widely studied and mathematically proven, they suffer from being very slow. In this context, we propose to use RL in…
Read More Enhanced Power Utilization for Grid Resource Providers
A grid is a system that can manage and organize services and resources that spread amongst different control domains, employ interfaces and protocols, and offer a high quality of services. The integration of Multi-Agent Systems (MAS) with a grid environment significantly affects grid performance. MAS is considered a suitable solution for open systems that modify…
Read More A New Distributed Reinforcement Learning Approach for Multiagent Cooperation Using Team-mate Modeling and Joint Action Generalization
This paper focuses on the issue of distributed reinforcement learning (RL) for decision-making in cooperative multi-agent systems. Although this problem has been a topic of interest to many researchers, results obtained from these works aren’t sufficient and several difficulties have not yet been resolved, such as, the curse of dimensionality and the multi-agent coordination problem.…
Read More A delay-dependent distributed SMC for stabilization of a networked robotic system exposed to external disturbances
In this paper, a delay-dependent controller based on the sliding mode concept is proposed to stabilize a networked robotic system in a decentralized synchronization scheme. In addition to being affected by communication time-delays between agents, and seen that external disturbances obviously affect any physical and dynamic system, an unsettling action resulting from measurement errors affects…
Read More