Sriraam Natarajan


Towards Problem Solving Agents that Communicate and Learn
Anjali Narayan-Chen | Colin Graber | Mayukh Das | Md Rakibul Islam | Soham Dan | Sriraam Natarajan | Janardhan Rao Doppa | Julia Hockenmaier | Martha Palmer | Dan Roth
Proceedings of the First Workshop on Language Grounding for Robotics

Agents that communicate back and forth with humans to help them execute non-linguistic tasks are a long sought goal of AI. These agents need to translate between utterances and actionable meaning representations that can be interpreted by task-specific problem solvers in a context-dependent manner. They should also be able to learn such actionable interpretations for new predicates on the fly. We define an agent architecture for this scenario and present a series of experiments in the Blocks World domain that illustrate how our architecture supports language learning and problem solving in this domain.


A Comparison of Weak Supervision methods for Knowledge Base Construction
Ameet Soni | Dileep Viswanathan | Niranjan Pachaiyappan | Sriraam Natarajan
Proceedings of the 5th Workshop on Automated Knowledge Base Construction