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Efficient Reinforcement Learning by Reducing Forgetting with Elephant Activation Functions
Qingfeng Lan, Gautham Vasan, A. Rupam Mahmood
Catastrophic forgetting has remained a significant challenge for efficient reinforcement learning for decades (Ring 1994, Rivest and Precup 2003). While recent works have proposed…
Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers
Gautham Vasan, Mohamed Elsayed, Alireza Azimi +5
Modern deep policy gradient methods achieve effective performance on simulated robotic tasks, but they all require large replay buffers or expensive batch updates, or both, making…
Streaming Deep Reinforcement Learning Finally Works
Mohamed Elsayed, Gautham Vasan, A. Rupam Mahmood
Natural intelligence processes experience as a continuous stream, sensing, acting, and learning moment-by-moment in real time. Streaming learning, the modus operandi of classic rei…
Autoregressive Policies for Continuous Control Deep Reinforcement Learning
Dmytro Korenkevych, A. Rupam Mahmood, Gautham Vasan +1
Reinforcement learning algorithms rely on exploration to discover new behaviors, which is typically achieved by following a stochastic policy. In continuous control tasks, policies…
Benchmarking Reinforcement Learning Algorithms on Real-World Robots
A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan +2
Through many recent successes in simulation, model-free reinforcement learning has emerged as a promising approach to solving continuous control robotic tasks. The research communi…