While the fault repair capability of Evolvable Hardware (EH) approaches have been previously demonstrated, further improvements to fault handling capability can be achieved by exp...
: An autonomic network must work unsupervised, therefore must be able to respond to unpredictable situations. The BIONETS project is working towards resilient network services that...
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
A new paradigm for online EH regeneration using Genetic Algorithms (GAs) called Competitive Runtime Reconfiguration (CRR) is developed where performance is assessed based upon a b...
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...