Cooperation logics have recently begun to attract attention within the multi-agent systems community. Using a cooperation logic, it is possible to represent and reason about the s...
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
The development of a low bandwidth, high error tolerant neural browser, called the BrainBrowser, has raised new navigational issues. With this paradigm shift of twodimensional spa...
Compositional Scheduling Analysis couples local scheduling analysis via event streams. While local analysis has successfully been extended to include hierarchical scheduling strat...
Recently, many research efforts are directed towards coevolutionary algorithms. The present work aims at the assessment of Hierarchical Cooperative CoEvolution (HCCE) being proper...