We consider a multi-agent optimization problem where agents aim to cooperatively minimize a sum of local objective functions subject to a global inequality constraint and a global ...
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Abstract. The deployment of agent societies —as complex systems— in dynamic and unpredictable settings brings forth critical issues concerning their design. Organizational mode...
Loris Penserini, Virginia Dignum, Athanasios Staik...
In many distributed computing systems that are prone to either induced or spontaneous node failures, the number of available computing resources is dynamically changing in a rando...
Sagar Dhakal, Majeed M. Hayat, Jorge E. Pezoa, Cha...
When developping multi-agent systems (MAS) or models in the context of agent-based simulation (ABS), the tuning of the model constitutes a crucial step of the design process. Indee...