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Explaining Creative Artifacts
Lav R. Varshney, Nazneen Fatema Rajani, Richard Socher
Human creativity is often described as the mental process of combining associative elements into a new form, but emerging computational creativity algorithms may not operate in thi…
Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards
Alexander Trott, Stephan Zheng, Caiming Xiong +1
While using shaped rewards can be beneficial when solving sparse reward tasks, their successful application often requires careful engineering and is problem specific. For instance…
Self-Monitoring Navigation Agent via Auxiliary Progress Estimation
Chih-Yao Ma, Jiasen Lu, Zuxuan Wu +4
The Vision-and-Language Navigation (VLN) task entails an agent following navigational instruction in photo-realistic unknown environments. This challenging task demands that the ag…
Multi-Hop Knowledge Graph Reasoning with Reward Shaping
Xi Victoria Lin, Richard Socher, Caiming Xiong
Multi-hop reasoning is an effective approach for query answering (QA) over incomplete knowledge graphs (KGs). The problem can be formulated in a reinforcement learning (RL) setup,…
Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning
Tianmin Shu, Caiming Xiong, Richard Socher
Learning policies for complex tasks that require multiple different skills is a major challenge in reinforcement learning (RL). It is also a requirement for its deployment in real-…
Weighted Transformer Network for Machine Translation
Karim Ahmed, Nitish Shirish Keskar, Richard Socher
State-of-the-art results on neural machine translation often use attentional sequence-to-sequence models with some form of convolution or recursion. Vaswani et al. (2017) propose a…