  In this extended abstract, we investigate the design of learning
representation for human intention inference. In our designed human intention
prediction task, we propose a history encoding representation that is both
interpretable and effective for prediction. Through extensive experiments, we
show our prediction framework with a history encoding representation design is
successful on the human intention prediction problem.
