10 citations · 10 across the 6 of their papers we have counts for
3 papers · 1 filter
Performance-Weighed Policy Sampling for Meta-Reinforcement Learning
Ibrahim Ahmed, Marcos Quinones-Grueiro, Gautam Biswas
This paper discusses an Enhanced Model-Agnostic Meta-Learning (E-MAML) algorithm that generates fast convergence of the policy function from a small number of training examples whe…
Complementary Meta-Reinforcement Learning for Fault-Adaptive Control
Ibrahim Ahmed, Marcos Quinones-Grueiro, Gautam Biswas
Faults are endemic to all systems. Adaptive fault-tolerant control maintains degraded performance when faults occur as opposed to unsafe conditions or catastrophic events. In syste…
A Relearning Approach to Reinforcement Learning for Control of Smart Buildings
Avisek Naug, Marcos Quiñones-Grueiro, Gautam Biswas
This paper demonstrates that continual relearning of control policies using incremental deep reinforcement learning (RL) can improve policy learning for non-stationary processes. W…