From 79e561f9e57ed155a953854c207fa8dabb36e6b4 Mon Sep 17 00:00:00 2001
From: Adam Jelley <47476156+AdamJelley@users.noreply.github.com>
Date: Mon, 2 Oct 2023 15:39:52 +0100
Subject: [PATCH] Update publications.md

Add "Contrastive Meta-Learning for Partially Observable Few-Shot Learning" by Jelley et al. (published at ICLR 2023) to list of publications.

Paper uses Minigrid to investigate learning an environment representation (map) from partial agent observations.
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 docs/content/publications.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/content/publications.md b/docs/content/publications.md
index 96ad4ab8e..48a3c90fb 100644
--- a/docs/content/publications.md
+++ b/docs/content/publications.md
@@ -10,6 +10,7 @@ List of publications & submissions using Minigrid or BabyAI (please open a pull
 - [Hierarchies of Reward Machines](https://arxiv.org/abs/2205.15752) (Imperial College London, ILASP, Universitat Pompeu Fabra, ICML 2023)
 - [Minimal Value-Equivalent Partial Models for Scalable and Robust Planning in Lifelong Reinforcement Learning](https://arxiv.org/abs/2301.10119) (Mila, McGill University, CoLLAs 2023)
 - [DEIR: Efficient and Robust Exploration through Discriminative-Model-Based Episodic Intrinsic Rewards](https://arxiv.org/abs/2304.10770) (U-Tokyo, Google Brain, IJCAI 2023)
+- [Contrastive Meta-Learning for Partially Observable Few-Shot Learning](https://arxiv.org/abs/2301.13136) (University of Edinburgh, Microsoft Research Cambridge, ICLR 2023)
 - [Towards Improving Exploration in Self-Imitation Learning using Intrinsic Motivation](https://arxiv.org/abs/2211.16838) (TECNALIA, IEEE ADPRL 2022)
 - [An Evaluation Study of Intrinsic Motivation Techniques applied to Reinforcement Learning over Hard Exploration Environments](https://arxiv.org/abs/2205.11184) (TECNALIA, CD-MAKE 2022)
 - [Evolution Strategies for Sparse Reward Gridworld Environments.](https://link.springer.com/chapter/10.1007/978-3-031-22695-3_19) (DSTG, AJCAI 2022)