The vision of this project (under the DARPA CwC grant) is to build smart machines that enable “Artificial Intelligence” agents and humans to interact seamlessly, make decisions and solve problems together and learn from each other as well as complement each others capabilities. An over-arching framework for human-machine collaboration involving multiple human (non)experts and machines through varied modalities and protocols of interaction. Concept learning/teaching, collaborative planning, domain transfer/extension and higher level knowledge induction are some of the avenues that we are presently investigating.
- Das, M., Odom, P., Islam, M.R., Doppa, J., Roth, D., & Natarajan, S., “Preference- Guided Planning: An Active Elicitation Approach”, International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018.
- Das, M., Islam, M.R., Doppa, J.R., Roth, D., & Natarajan, S., “Active Preference Elicitation for Planning”, Human-Machine Collaborative Learning workshop(@ AAAI) 2017.
- Narayan-Chen A., Graber C., Das M., Islam M.R., Dan S., Natarajan S., Doppa J.R., Hockenmaier J., Palmer M., Roth D., “Towards Problem Solving Agents that Communicate and Learn.” Workshop on Language Grounding for Robotics at ACL 2017.