MB-MPO — Model-Based Meta-Policy Optimization

Discussion on an algorithm that efficiently learns a robust policy by applying MAML to multiple dynamics model.

ProMP — Proximal MetaPolicy Search

We address the credit assignment problem of two forms of MAML with an RL objective and discuss an efficient and stable meta reinforcement learning algorithm.

Adaptive MAML — Applying MAML-RL to nonstationary environments

Discussion on a variant of MAML-RL for solving tasks that change dynamically due to non-stationary of the environment.

MAML++: Improvements on MAML

Discussion on a series of improvements on MAML

MAML — Model-Agnostic Meta-Learning

Discussion on an optimization algorithm for meta-learning named Model-Agnostic Meta-Learning(MAML)

SNAIL — Simple Neural AttentIve meta-Learner

Discussion on a meta-learning architecture named Simple Neural AttentIve meta-Learner(SNAIL).

HAC — Learning Multi-Level Hierarchies with Hindsight

A norvel hierarchical reinforcement learning frame work that can efficiently learn multiple levels of policies in parallel.

NORL-HRL — Near-Optimal Representation Learning for Hierarchical Reinforcement Learning

Near-Optimal Representation Learning for Hierarchical Reinforcement Learning: An improvement to HIRO

HIRO — HIerarchical Reinforcement learning with Off-policy correction

Discussion on a hierarchical reinforcement learning algorithm for goal-directed tasks.

Hierarchical Guidance

Discussion on an algorithmic framework called hierarchical guidance, which leverages hierarchical structure in imitation learning.