Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
This work presents an approach to the obstacle avoidance problem, applicable in the frame of driver assistance. A decision, expressed as a proposed acceleration vector for the veh...
Franck Gechter, Jean-Michel Contet, Pablo Gruer, A...
In the realization of agent-based applications the developer generally needs to use heterogeneous agent architectures, so that each application component can optimally perform its...
This paper presents an innovative multi-agent system development approach called mission-based on-demand agent generation. This approach allows agents to be dynamically composed at...
Glenn T. Jayaputera, Arkady B. Zaslavsky, Seng Wai...