Considerable interest in the hypothesis that different cognitive tasks recruit qualitatively distinct processing systems has led to the proposal of separate explicit (declarative) and implicit (procedural) systems. A popular probabilistic category learning task known as the weather prediction task is said to be ideally suited to examine this distinction because its two versions, "observation" a...

As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches, retrieval systems can learn directly from implicit feedback, while they are running. In such an online setting, algorithms need to both explore new solutions to obtain feedback for effective learning, and exploit what has alr...

Formative feedback for a learner typically uses human or artificial intelligence to draw an inference about a learner’s knowledge state from the learner’s actions, and select a learner-directed response. To tackle cases when such intelligence is not easily available, we are exploring ways of providing implicit formative feedback: A learner’s action is to respond to an explanation prompt, and th...

This paper illustrates the activity conducted at the TREC 2005 evaluation campaign in the ad-hoc task of the Genomics track. The retrieval effectiveness of a relevance feedback query expansion algorithm, which is based on symbols, is studied. The experimental results suggest that query expansion based on implicit relevance feedback is not always an effective means for improving effectiveness in...

Reactions such as gestures, facial expressions, and vocalizations are an abundant, naturally occurring channel of information that humans provide during interactions. An agent could leverage understanding implicit human feedback to improve its task performance at no cost the human. This approach contrasts with common teaching methods based on demonstrations, critiques, or other guidance need be...