Energy efficiency and collisions avoidance are both critical properties to increase the lifetime and effectiveness of wireless networks. This paper proposes a family of algorithms...
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Increased complexity of memory systems to ameliorate the gap between the speed of processors and memory has made it increasingly harder for compilers to optimize an arbitrary code...
vices provide an important abstract layer on top of heterogeneous components (hardware and software) that take part into a grid environment. In this scenario, applications, like sc...
This paper discusses the implementation of local search in evolutionary multiobjective optimization (EMO) algorithms for the design of a simple but powerful memetic EMO algorithm. ...