Our paper “TreeQN and ATreeC: Differentiable Tree Planning for Deep Reinforcement Learning” has been accepted at #ICLR2018 ! Congratulations to Gregory Farquhar, Tim Rocktäschel, Maximilian Igl and Shimon Whiteson.
We’re happy to announce that WhiRL members have two accepted papers at #AAMAS2018 this year.Learning with Opponent-Learning Awareness Jakob N. Foerster, Richard Y. Chen, Maruan Al-Shedivat, Shimon Whiteson, Pieter Abbeel, Igor Mordatch. Arxiv version: https://arxiv.org/abs/1709.04326 Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making, Luisa M Zintgraf, Diederik M Roijers, Sjoerd Linders, Catholijn M Jonker, Ann Nowé (to be published soon)
Whiteson Research Lab members have three papers accepted at AAAI-2018: Counterfactual Multi-Agent Policy GradientsJakob Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, Shimon WhitesonAlternating Optimisation and Quadrature for Robust ControlSupratik Paul, Shimon Whiteson, Michael Osborne, Konstantinos Chatzilygeroudis, Kamil Ciosek, Jean-Baptiste MouretExpected Policy GradientsKamil Ciosek, Shimon Whiteson
Whiteson Research Lab members have three papers accepted at NIPS-2017: Utile Context Tree Weighting João Messias and Shimon Whiteson End-to-end Differentiable Proving Tim Rocktäschel and Sebastian Riedel Cortical Microcircuits as Gated-Recurrent Neural Networks Rui Ponte Costa, Yannis Assael, Brendan Shillingford, Nando de Freitas, Tim Vogels
WhiRL members have contributed three papers to this year’s ICML: Stabilising Experience Replay for Deep Multi−Agent Reinforcement Learning Programming with a Differentiable Forth Interpreter Input Switched Affine Networks: An RNN Architecture Designed for Interpretability