In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
EEG-based brain computer interface (BCI) provides a new communication channel between the human brain and a computer. The classification of EEG data is an important task in EEG-ba...
Gholamreza Salimi Khorshidi, Ayyoub Jaafari, Ali M...
Multi Agent Based Simulation (MABS) has been used mostly in purely social contexts. However, compared to other approaches, e.g., traditional discrete event simulation, object-orien...
Systems often exhibit hierarchical structures and multiple levels of abstraction, and MultiAgent Systems, even if they have proved their adequacy to model such systems, mains in t...
Sebastian Rodriguez, Nicolas Gaud, Vincent Hilaire...
This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...