In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
The need for supporting CSCW applications with heterogeneous and varying user requirements call for adaptive and reconfigurable schedulers accommodating a mixture of real-time, pro...
Scheduling collective communications (CC) in networks based on optimal graphs and digraphs has been done with the use of the evolutionary techniques. Inter-node communication patt...
In practical system identification, process optimization and controller design, it is often desirable to simultaneously handle several objectives and constraints. In some cases, t...
This paper proposes a few steps to escape structured extensive representations for objects, in the context of evolutionary Topological Optimum Design (TOD) problems: early results ...