research
∙
05/18/2022
Policy Distillation with Selective Input Gradient Regularization for Efficient Interpretability
Although deep Reinforcement Learning (RL) has proven successful in a wid...
share
research
∙
02/25/2021
Neuroevolution of a Recurrent Neural Network for Spatial and Working Memory in a Simulated Robotic Environment
Animals ranging from rats to humans can demonstrate cognitive map capabi...
research
∙
02/11/2021
A complete neuromorphic solution to outdoor navigation and path planning
Recent developments in neuromorphic engineering have enabled low-powered...
research
∙
02/11/2021
Advantage of prediction and mental imagery for goal‐directed behaviour in agents and robots
Mental imagery and planning are important aspects of cognitive behaviour...
research
∙
02/11/2021
Neurorobots as a Means Toward Neuroethology and Explainable AI
Understanding why deep neural networks and machine learning algorithms a...
research
∙
02/11/2021
Neuromodulated attention and goal-driven perception in uncertain domains
In uncertain domains, the goals are often unknown and need to be predict...
research
∙
02/11/2021
Terrain Classification with a Reservoir-Based Network of Spiking Neurons
Terrain classification is important for outdoor path planning, mapping, ...
research
∙
02/10/2021
Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation
Despite the recent success of deep reinforcement learning (RL), domain a...
research
∙
09/14/2019
Neuromodulated Patience for Robot and Self-Driving Vehicle Navigation
Robots and self-driving vehicles face a number of challenges when naviga...
research
∙
03/02/2019
Attention-Based Structural-Plasticity
Catastrophic forgetting/interference is a critical problem for lifelong ...
research
∙
02/16/2019
