C. Ong

activity

20242026

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Showing 2024Show all

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cs.LG2024

Reinforcement Learning with LTL and $ω$ -Regular Objectives via Optimality-Preserving Translation to Average Rewards

Xuan-Bach Le, Dominik Wagner, Leon Witzman +2

Linear temporal logic (LTL) and, more generally, $ω$ -regular objectives are alternatives to the traditional discount sum and average reward objectives in reinforcement learning (RL…

cs.LG2024

Diagonalisation SGD: Fast & Convergent SGD for Non-Differentiable Models via Reparameterisation and Smoothing

Dominik Wagner, Basim Khajwal, C. -H. Luke Ong

It is well-known that the reparameterisation gradient estimator, which exhibits low variance in practice, is biased for non-differentiable models. This may compromise correctness o…

Reinforcement Learning with LTL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards

Diagonalisation SGD: Fast & Convergent SGD for Non-Differentiable Models via Reparameterisation and Smoothing

Reinforcement Learning with LTL and $ω$ -Regular Objectives via Optimality-Preserving Translation to Average Rewards