Cooperative multi-agent systems (MAS) are finding applications in a wide variety of domains, including sensor networks, robotics, distributed control, collaborative decision support systems, and data mining. A cooperative MAS consists of a group of autonomous agents that interact with one another in order to optimize a global performance measure. A central challenge in cooperative MAS research is to design distributed coordination policies. Designing optimal distributed coordination policies offline is usually not feasible for large-scale complex multi-agent systems, where 10s to 1000s of agents are involved, there is limited communication bandwidth and communication delay between agents, agents have only limited partial views of the whole ...
Multiagent Reinforcement Learning (MARL) is a promising technique for agents learning effective coor...
Abstract—Coordinating multi-agent reinforcement learning provides a promising approach to scaling le...
In the present work, distributed control and artificial intelligence are combined in a control archi...
Cooperative multi-agent systems (MAS) are finding applications in a wide variety of domains, includi...
A growing number of real-world control problems require teams of software agents to solve a joint ta...
A plethora of real world problems, such as the control of autonomous vehicles and drones, packet de...
Reinforcement learning techniques have been successfully used to solve single agent optimization pro...
In many multi-agent applications such as distributed sensor nets, a network of agents act collaborat...
Cooperative multi-agent reinforcement learning (MARL) has achieved significant results, most notably...
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergenc...
AbstractCoordination among multiple autonomous, distributed cognitive agents is one of the most chal...
Cooperative multi-agent systems problems are ones in which several agents attempt, through their int...
Research Doctorate - Doctor of Philosophy (PhD)Machine learning in multi-agent domains poses several...
Abstract Multi-agent systems are rapidly nding applications in a variety of domains, including robo...
As progress in reinforcement learning (RL) gives rise to increasingly general and powerful artificia...
Multiagent Reinforcement Learning (MARL) is a promising technique for agents learning effective coor...
Abstract—Coordinating multi-agent reinforcement learning provides a promising approach to scaling le...
In the present work, distributed control and artificial intelligence are combined in a control archi...
Cooperative multi-agent systems (MAS) are finding applications in a wide variety of domains, includi...
A growing number of real-world control problems require teams of software agents to solve a joint ta...
A plethora of real world problems, such as the control of autonomous vehicles and drones, packet de...
Reinforcement learning techniques have been successfully used to solve single agent optimization pro...
In many multi-agent applications such as distributed sensor nets, a network of agents act collaborat...
Cooperative multi-agent reinforcement learning (MARL) has achieved significant results, most notably...
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergenc...
AbstractCoordination among multiple autonomous, distributed cognitive agents is one of the most chal...
Cooperative multi-agent systems problems are ones in which several agents attempt, through their int...
Research Doctorate - Doctor of Philosophy (PhD)Machine learning in multi-agent domains poses several...
Abstract Multi-agent systems are rapidly nding applications in a variety of domains, including robo...
As progress in reinforcement learning (RL) gives rise to increasingly general and powerful artificia...
Multiagent Reinforcement Learning (MARL) is a promising technique for agents learning effective coor...
Abstract—Coordinating multi-agent reinforcement learning provides a promising approach to scaling le...
In the present work, distributed control and artificial intelligence are combined in a control archi...