3 papers
cs.RO2026
When a Robot is More Capable than a Human: Learning from Constrained Demonstrators
Xinhu Li, Ayush Jain, Zhaojing Yang +2
Learning from demonstrations enables experts to teach robots complex tasks using interfaces such as kinesthetic teaching, joystick control, and sim-to-real transfer. However, these…
cs.LG2025
Actor-Free Continuous Control via Structurally Maximizable Q-Functions
Yigit Korkmaz, Urvi Bhuwania, Ayush Jain +1
Value-based algorithms are a cornerstone of off-policy reinforcement learning due to their simplicity and training stability. However, their use has traditionally been restricted t…
cs.LG2025
Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions
Ayush Jain, Norio Kosaka, Xinhu Li +3
In reinforcement learning, off-policy actor-critic methods like DDPG and TD3 use deterministic policy gradients: the Q-function is learned from environment data, while the actor ma…