Due to increasing clock speeds and shrinking technologies, distributing a single global clock signal throughout a chip is becoming a difficult and challenging proposition. In this...
Most models of decision-making in neuroscience assume an infinite horizon, which yields an optimal solution that integrates evidence up to a fixed decision threshold; however, u...
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
A common feature of congestion control protocols is the presence of information packets used to signal congestion. We address here the question of how frequently such protocols nee...
We present a new approach to the supervised learning of lateral interactions for the competitive layer model (CLM) dynamic feature binding architecture. The method is based on con...