RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
In possibility theory, the degree of inconsistency is commonly used to measure the level of conflict in information from multiple sources after merging, especially conjunctive merg...
We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between...
In previous work, we reported dramatic improvements in automatic speech recognition (ASR) and spoken language translation (SLT) gained by applying information extracted from spoke...
The history of the human race is one of increasing intellectual capability. Since the time of our early ancestors, our brains have gotten no bigger; nevertheless, there has been a...