4 citations · 4 across the 4 of their papers we have counts for
6 papers
Policy Distillation with Selective Input Gradient Regularization for Efficient Interpretability
Jinwei Xing, Takashi Nagata, Xinyun Zou +2
Although deep Reinforcement Learning (RL) has proven successful in a wide range of tasks, one challenge it faces is interpretability when applied to real-world problems. Saliency m…
Neuroevolution of a Recurrent Neural Network for Spatial and Working Memory in a Simulated Robotic Environment
Xinyun Zou, Eric O. Scott, Alexander B. Johnson +4
Animals ranging from rats to humans can demonstrate cognitive map capabilities. We evolved weights in a biologically plausible recurrent neural network (RNN) using an evolutionary…
Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation
Jinwei Xing, Takashi Nagata, Kexin Chen +3
Despite the recent success of deep reinforcement learning (RL), domain adaptation remains an open problem. Although the generalization ability of RL agents is critical for the real…
Neuromodulated Patience for Robot and Self-Driving Vehicle Navigation
Jinwei Xing, Xinyun Zou, Jeffrey L. Krichmar
Robots and self-driving vehicles face a number of challenges when navigating through real environments. Successful navigation in dynamic environments requires prioritizing subtasks…
Attention-Based Structural-Plasticity
Soheil Kolouri, Nicholas Ketz, Xinyun Zou +2
Catastrophic forgetting/interference is a critical problem for lifelong learning machines, which impedes the agents from maintaining their previously learned knowledge while learni…
Neuromodulated Goal-Driven Perception in Uncertain Domains
Xinyun Zou, Soheil Kolouri, Praveen K. Pilly +1
In uncertain domains, the goals are often unknown and need to be predicted by the organism or system. In this paper, contrastive excitation backprop (c-EB) was used in a goal-drive…