1st Workshop on Goal Specifications for Reinforcement Learning
https://sites.google.com/view/goalsrl/accepted-papers?authuser=0

Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition.

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills.

Challenging the MDP Status Quo: An Axiomatic Approach to Rationality for Reinforcement Learning Agents.

Recurrent Existence Determination Through Policy Optimization.

Multi-Task Maximum Causal Entropy Inverse Reinforcement Learning.

Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning.

Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning.

Augmenting Experience via Teachers' Advice.

Diversity is All You Need: Learning Skills without a Reward Function.

Exploring Hierarchy-Aware Inverse Reinforcement Learning.

Learning a Prior over Intent via Meta-Inverse Reinforcement Learning.

Unsupervised Meta-Learning for Reinforcement Learning.

Multi-Agent Generative Adversarial Imitation Learning.

SILC : Smoother Imitation with Lipschitz Costs.

Active Inverse Reward Design.

Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping (Extended Version).

Few-Shot Goal Inference for Visuomotor Learning and Planning.