In this paper, we show that a Bio-inspired classifier’s accuracy can be dramatically improved if it operates on intelligent features. We propose a novel set of intelligent feat...
M. Zubair Shafiq, Syed Ali Khayam, Muddassar Faroo...
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
In this paper, we describe a rote extractor that learns patterns for finding semantic relationships in unrestricted text, with new procedures for pattern generalization and scorin...
Enrique Alfonseca, Pablo Castells, Manabu Okumura,...
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...