this paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (mimo) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. the agents may have different dynamics and communicate together under a directed graph. a distributed adaptive method is designed for both cases. the structures of the contro...

Maritime surveillance is a difficult task as its aim is to detect any threatening event in a dynamic, complex and hugely distributed system. As there are many different types of vessels, behaviours, situations, and because the system is constantly evolving, classical automated surveillance approaches are unrealistic. We propose an adaptive multi-agent system in which each agent is responsible f...

Aphasia diagnosis is a challenging medical diagnostic task due to the linguistic uncertainty and vagueness, large number of measurements with imprecision, inconsistencies in the definition of Aphasic syndromes, natural diversity and subjectivity in test objects as well as in options of experts who diagnose the disease. In this paper we present a new self-organized multi agent system that diagno...

We consider a team of agents that are required to coordinate their actions in order to maximize a global objective. Our domains are characterized by uncertainty, dynamism, and distributed information. Determining appropriate actions becomes quite difficult, especially as the number of agents and the coupling between them increases. This paper discusses four contributions toward the goal of coor...

Swarm robotic systems are currently being used to address many real-world problems. One interesting application of swarm robotics is the self-organized formation of structures and shapes. Some of the key challenges in the swarm robotic systems include swarm size constraint, random motion, coordination among robots, localization, and adaptability in a decentralized environment. Rubenstein et al....

multi agent markov decision processes (mmdps), as the generalization of markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for multi agent reinforcement learning. in this paper, a generalized learning automata based algorithm for finding optimal policies in mmdp is proposed. in the proposed algorithm, mmdp ...

in this paper, the optimal adaptive leader-follower consensus of linear continuous time multi-agent systems is considered. the error dynamics of each player depends on its neighbors’ information. detailed analysis of online optimal leader-follower consensus under known and unknown dynamics is presented. the introduced reinforcement learning-based algorithms learn online the approximate solution...

Nowadays, multi-agent systems are frequently used to control big components of IT systems. Since this systems are big and use and produce big data, the control of multi-agents systems by people is not beneficial anymore. So, self-organization, in which agents can organize themselves, is proposed as a resolution. In a self-organizing multi-agent system, the desired behavior of system is emerged ...