, On evaluation of embodied navigation agents, 2018.

Optimal control of markov processes with incomplete state information, Journal of Mathematical Analysis and Applications, vol.10, issue.1, pp.174-205, 1965. ,

Interaction networks for learning about objects, relations and physics, Advances in neural information processing systems, pp.4502-4510, 2016. ,

, Relational inductive biases, deep learning, and graph networks, 2018.

, Relational inductive biases, deep learning, and graph networks, 2018.

, Egomap: Projective mapping and structured egocentric memory for deep rl, 2020.

URL : https://hal.archives-ouvertes.fr/hal-02864146

On a routing problem, Quarterly of applied mathematics, vol.16, issue.1, pp.87-90, 1958. ,

Playing doom with slam-augmented deep reinforcement learning, 2016. ,

Geometric deep learning: going beyond euclidean data, IEEE Signal Processing Magazine, vol.34, issue.4, pp.18-42, 2017. ,

Learning to explore using active neural slam, International Conference on Learning Representations, 2020. ,

Learning exploration policies for navigation, International Conference on Learning Representations, 2019. ,

Empirical evaluation of gated recurrent neural networks on sequence modeling, 2014. ,

, Gated Feedback Recurrent Neural Networks. In: ICML, 2015.

Language modeling with gated convolutional networks, Proceedings of the 34th International Conference on Machine Learning, vol.70, pp.933-941, 2017. ,

A note on two problems in connexion with graphs, Numerische mathematik, vol.1, issue.1, pp.269-271, 1959. ,

Search on the replay buffer: Bridging planning and reinforcement learning, Advances in Neural Information Processing Systems, vol.32, pp.15220-15231, 2019. ,

Protein interface prediction using graph convolutional networks, Advances in neural information processing systems, pp.6530-6539, 2017. ,

Neural message passing for quantum chemistry, Proceedings of the 34th International Conference on Machine Learning, vol.70, pp.1263-1272, 2017. ,

, Neural turing machines, 2014.

Hybrid computing using a neural network with dynamic external memory, Nature, vol.538, issue.7626, p.471, 2016. ,

Cognitive mapping and planning for visual navigation, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.7272-7281, 2017. ,

,

Unifying map and landmark based representations for visual navigation, 2017. ,

Long Short-Term Memory, Neural Computation, vol.9, issue.8, pp.1735-1780, 1997. ,

Reinforcement learning with unsupervised auxiliary tasks, 2017. ,

An efficient graph convolutional network technique for the travelling salesman problem, 2019. ,

Planning and acting in partially observable stochastic domains, Artificial intelligence, vol.101, issue.1-2, pp.99-134, 1998. ,

, Qmdp-net: Deep learning for planning under partial observability, 2017.

ViZ-Doom: A Doom-based AI research platform for visual reinforcement learning, IEEE Conference on Computatonal Intelligence and Games, 2017. ,

,

Semi-supervised classification with graph convolutional networks, International Conference on Learning Representations, 2017. ,

Sarsop: Efficient point-based pomdp planning by approximating optimally reachable belief spaces, Proc. Robotics: Science and Systems, 2008. ,

Planning algorithms, 2006. ,

URL : https://hal.archives-ouvertes.fr/hal-01993243

Gradient-Based Learning Applied to Document Recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998. ,

Combinatorial optimization with graph convolutional networks and guided tree search, Advances in Neural Information Processing Systems, pp.539-548, 2018. ,

Habitat: A Platform for Embodied AI Research, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019. ,

Learning to Navigate in Cities Without a Map, 2018. ,

Learning to Navigate in Complex Environments, 2017. ,

Human-level control through deep reinforcement learning, Nature, vol.518, issue.7540, 2015. ,

Human-level control through deep reinforcement learning, Nature, vol.518, 2015. ,

Moddrop: adaptive multi-modal gesture recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.38, issue.8, pp.1692-1706, 2015. ,

URL : https://hal.archives-ouvertes.fr/hal-01178733

Neural map: Structured memory for deep reinforcement learning, 2018. ,

Pytorch: An imperative style, high-performance deep learning library ,

, Advances in Neural Information Processing Systems, vol.32, pp.8024-8035, 2019.

Towards a general theory of topological maps, Artif. Intell, vol.152, pp.47-104, 2004. ,

Semi-parametric topological memory for navigation, International Conference on Learning Representations, 2018. ,

Modeling relational data with graph convolutional networks, European Semantic Web Conference, pp.593-607, 2018. ,

, Proximal policy optimization algorithms, 2017.

, Proximal policy optimization algorithms, 2017.

A survey of point-based pomdp solvers, Autonomous Agents and Multi-Agent Systems, vol.27, issue.1, pp.1-51, 2013. ,

Learning topological maps with weak local odometric information, pp.920-929, 1997. ,

A general reinforcement learning algorithm that masters chess, shogi, and go through self-play, Science, vol.362, issue.6419, pp.1140-1144, 2018. ,

The optimal control of partially observable markov processes over a finite horizon, Operations research, vol.21, issue.5, pp.1071-1088, 1973. ,

Heuristic search value iteration for pomdps, Proceedings of the 20th conference on Uncertainty in artificial intelligence, pp.520-527, 2004. ,

, Universal planning networks, 2018.

, Value iteration networks, 2016.

Learning metric-topological maps for indoor mobile robot navigation, Artificial Intelligence, vol.99, issue.1, pp.21-71, 1998. ,

Human spatial representation: Insights from animals, Trends in Cognitive Sciences, vol.6, issue.9, pp.1961-1968, 2002. ,

Unsupervised predictive memory in a goal-directed agent, 2018. ,

, A comprehensive survey on graph neural networks, 2019.

Gibson env: realworld perception for embodied agents, Computer Vision and Pattern Recognition (CVPR), 2018. ,

, What can neural networks reason about? arxiv preprint 1905, p.13211, 2019.

, What can neural networks reason about, 2019.

, Neural SLAM, 2017.

, Graph neural networks: A review of methods and applications, 2018.

Target-driven visual navigation in indoor scenes using deep reinforcement learning, 2017 IEEE international conference on robotics and automation (ICRA), pp.3357-3364, 2017. ,