Artificial intelligence publications

I will first illuminate the problem, and then demonstrate two potential solutions in terms of macro refactoring techniques. These techniques can be applied in related scenarios.

This article describes a coordinated set of bioinformatics databases and software tools designed to solve multiple problems faced by metabolic engineers and microbiologists related to metabolic pathways.

We approach the problem of understanding how people interact with each other in collaborative settings via Multiagent Inverse Reinforcement Learning (MIRL), where the goal is to infer the reward functions guiding the behavior of each individual given trajectories of a team’s behavior during some task.

This article offers thoughts on reviewing grant proposals for biological knowledgebases and databases (KDs) in the hope of aiding grant reviewers and applicants in addressing the issue of innovation.

Our new framework provides various measures of RL agent competence stemming from interestingness analysis and is applicable to a wide range of RL algorithms.

We simulate the process of corpus review and word list creation, showing that several simple interventions greatly improve recall as a function of simulated labor.

We present a framework for learning comprehensible models of sequential decision tasks in which agent strategies are characterized using temporal logic formulas.

We describe a large-scale experiment in which non-artificial intelligence subject matter experts (SMEs)—with neither artificial intelligence background nor extensive training in the task—author knowledge bases (KBs) following a challenge problem specification with a strong question-answering component.