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.
Artificial intelligence publications
BioCyc: Metabolic Pathway Databases and Informatics Tools
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.
Multiagent Inverse Reinforcement Learning via Theory of Mind Reasoning
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.
Reviewing Knowledgebase and Database Grant Proposals in the Life Sciences: The Role of Innovation
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.
Sensor Control for Information Gain in Dynamic, Sparse and Partially Observed Environments
We present an approach for autonomous sensor control for information gathering under partially observable, dynamic and sparsely sampled environments.
Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning
Our new framework provides various measures of RL agent competence stemming from interestingness analysis and is applicable to a wide range of RL algorithms.
Accelerating Human Authorship of Information Extraction Rules
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.
A Framework for understanding and Visualizing Strategies of RL Agents
We present a framework for learning comprehensible models of sequential decision tasks in which agent strategies are characterized using temporal logic formulas.
Experimental Evaluation of Subject Matter Expert-Oriented Knowledge Base Authoring Tools
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.