This paper argues that multiagent learning is a potential “killer application” for generative and developmental systems (GDS) because key challenges in learning to coordinate ...
Abstract Multi-agent systems (MASs) is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexiti...
Pieter Jan't Hoen, Karl Tuyls, Liviu Panait, Sean ...
This paper presents a role-based agent teamwork language called RoB-MALLET (Role-Based Multi-Agent Logic Language for Encoding Teamwork). Roles have been used to form multi-agent t...
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
— A distributed feedback control architecture that guarantees collision avoidance and destination convergence for multiple sphere world holonomic agents is presented. The well es...
Dimos V. Dimarogonas, Kostas J. Kyriakopoulos, Dim...