Learning during backtrack search is a space-intensive process that records information (such as additional constraints) in order to avoid redundant work. In this paper, we analyze...
Abstract. The growth in amount of data available today has encouraged the development of effective data analysis methods to support human decision-making. Neuro-fuzzy computation ...
: The paper presents results on the runtime complexity of two ant colony optimization (ACO) algorithms: Ant System, the oldest ACO variant, and GBAS, the first ACO variant for whic...
This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
This letter presents a new method to directly analyze and optimize symbol error rate (SER) performance of minimum decoding complexity (MDC) ABBA space-time block codes based on a t...