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04/12/2023
DiscoGen: Learning to Discover Gene Regulatory Networks
Accurately inferring Gene Regulatory Networks (GRNs) is a critical and c...
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02/09/2023
Equivariant MuZero
Deep reinforcement learning repeatedly succeeds in closed, well-defined ...
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02/08/2023
Investigating the role of model-based learning in exploration and transfer
State of the art reinforcement learning has enabled training agents on t...
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01/13/2023
Laser: Latent Set Representations for 3D Generative Modeling
NeRF provides unparalleled fidelity of novel view synthesis: rendering a...
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06/10/2022
Large-Scale Retrieval for Reinforcement Learning
Effective decision making involves flexibly relating past experiences an...
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04/11/2022
Learning to Induce Causal Structure
The fundamental challenge in causal induction is to infer the underlying...
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02/17/2022
Retrieval-Augmented Reinforcement Learning
Most deep reinforcement learning (RL) algorithms distill experience into...
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11/02/2021
Procedural Generalization by Planning with Self-Supervised World Models
One of the key promises of model-based reinforcement learning is the abi...
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04/13/2021
Muesli: Combining Improvements in Policy Optimization
We propose a novel policy update that combines regularized policy optimi...
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02/24/2021
Synthetic Returns for Long-Term Credit Assignment
Since the earliest days of reinforcement learning, the workhorse method ...
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02/03/2021
Neural Recursive Belief States in Multi-Agent Reinforcement Learning
In multi-agent reinforcement learning, the problem of learning to act is...
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12/14/2020
A case for new neural network smoothness constraints
How sensitive should machine learning models be to input changes? We tac...
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11/18/2020
Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Credit assignment in reinforcement learning is the problem of measuring ...
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11/08/2020
On the role of planning in model-based deep reinforcement learning
Model-based planning is often thought to be necessary for deep, careful ...
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10/03/2020
Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban
Intelligent robots need to achieve abstract objectives using concrete, s...
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09/11/2020
Physically Embedded Planning Problems: New Challenges for Reinforcement Learning
Recent work in deep reinforcement learning (RL) has produced algorithms ...
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04/23/2020
Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning
Standard planners for sequential decision making (including Monte Carlo ...
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02/19/2020
Value-driven Hindsight Modelling
Value estimation is a critical component of the reinforcement learning (...
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02/07/2020
Causally Correct Partial Models for Reinforcement Learning
In reinforcement learning, we can learn a model of future observations a...
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12/05/2019
Combining Q-Learning and Search with Amortized Value Estimates
We introduce "Search with Amortized Value Estimates" (SAVE), an approach...
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10/15/2019
Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions
A plethora of problems in AI, engineering and the sciences are naturally...
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10/02/2019
Unsupervised Doodling and Painting with Improved SPIRAL
We investigate using reinforcement learning agents as generative models ...
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01/11/2019
An investigation of model-free planning
The field of reinforcement learning (RL) is facing increasingly challeng...
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01/07/2019
Credit Assignment Techniques in Stochastic Computation Graphs
Stochastic computation graphs (SCGs) provide a formalism to represent st...
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11/27/2018
Single-Agent Policy Tree Search With Guarantees
We introduce two novel tree search algorithms that use a policy to guide...
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11/15/2018
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
Learning policies on data synthesized by models can in principle quench ...
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06/05/2018
Relational recurrent neural networks
Memory-based neural networks model temporal data by leveraging an abilit...
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02/13/2018
Learning to Search with MCTSnets
Planning problems are among the most important and well-studied problems...
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02/08/2018
Learning and Querying Fast Generative Models for Reinforcement Learning
A key challenge in model-based reinforcement learning (RL) is to synthes...
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07/19/2017
Imagination-Augmented Agents for Deep Reinforcement Learning
We introduce Imagination-Augmented Agents (I2As), a novel architecture f...
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07/19/2017
Learning model-based planning from scratch
Conventional wisdom holds that model-based planning is a powerful approa...
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06/05/2017
Visual Interaction Networks
From just a glance, humans can make rich predictions about the future st...
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03/28/2016
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models
We present a framework for efficient inference in structured image model...
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12/24/2015
Deep Reinforcement Learning in Large Discrete Action Spaces
Being able to reason in an environment with a large number of discrete a...
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01/07/2013
