We encourage submissions covering new ideas in interactive learning, reports on research in progress as well as discussions of open problems and challenges facing interactive machine learning. We are particularly interested in research regarding the practical application of interactive learning systems (for robotics, virtual agents, online education, dialog systems, health care, security, transportation, etc.), and the ability of these systems to handle the complexity of real world problems. We also encourage submissions bringing perspectives from the fields of psychology and social science, and from human computer interaction.
Topics relevant to this workshop include:
- Human-robot interaction
- Collaborative and/or shared control
- Semi-supervised learning with human intervention
- Learning from demonstration, interaction and/or observation
- Reinforcement learning with human-in-the-loop
- Active learning, Preference learning
- Transfer learning (human-to-machine, machine-to-machine)
- Natural language processing for dialog systems
- Computer vision for human interaction with autonomous systems
- Transparency and feedback in machine learning
- Computational models of human teaching
- Intelligent personal assistants and dialog systems
- Adaptive user interfaces
- Brain-computer interfaces (e.g. human-semi-autonomous system interfaces)
- Intelligent medical robots (e.g. smart wheelchairs, prosthetics, exoskeletons)
Authors are invited to submit long papers (8 pages for main text and 1 page for references) or short papers (2 to 4 pages for main text and 1 page for references) on research relevant to the theme of the workshop. The papers should be formatted according to NIPS formatting guidelines and submitted as a PDF document. All submissions are handled electronically through EasyChair. The submission deadline is Oct 14th 2016 (11:59 PM AoE, Anywhere on Earth).
Papers will be subject to a single-blind peer review, i.e. authors can keep their names and affiliations on their submitted papers. Papers will be evaluated based on originality, technical soundness, clarity and potential impact on the field of interactive machine learning. Accepted papers will be made publicly available on the workshop website. Accepted papers will be presented as talks and/or posters at the workshop.