Simulation-based training in complex decision making often requires ample personnel for playing various roles (e.g. team mates, adversaries). Using intelligent agents may diminish ...
Karel van den Bosch, Maaike Harbers, Annerieke Heu...
Neuroevolution is a promising learning method in tasks with extremely large state and action spaces and hidden states. Recent advances allow neuroevolution to take place in real t...
Chern Han Yong, Kenneth O. Stanley, Risto Miikkula...
In this paper, we present a new trajectory planning algorithm for virtual humans. Our approach focuses on implicit cooperation between multiple virtual agents in order to share th...
This paper presents a multi-agent framework designed to simulate synthetic humans that properly balance task oriented and social behaviors. The work presented in this paper focuses...
Francisco Grimaldo, Miguel Lozano, Fernando Barber
A novel technique for accurately and inexpensively simulating large numbers of people is introduced: Massively Multiplayer Online Human In the Loop Simulation (MMOHILS). This tech...