78 citations · 436 across the 23 of their papers we have counts for
5 papers · 1 filter
Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions
Lars Buesing, Nicolas Heess, Theophane Weber
A plethora of problems in AI, engineering and the sciences are naturally formalized as inference in discrete probabilistic models. Exact inference is often prohibitively expensive,…
Unsupervised Doodling and Painting with Improved SPIRAL
John F. J. Mellor, Eunbyung Park, Yaroslav Ganin +7
We investigate using reinforcement learning agents as generative models of images (extending arXiv:1804.01118). A generative agent controls a simulated painting environment, and is…
What can the brain teach us about building artificial intelligence?
Dileep George
This paper is the preprint of an invited commentary on Lake et al's Behavioral and Brain Sciences article titled "Building machines that learn and think like people". Lake et al's…
Credit Assignment Techniques in Stochastic Computation Graphs
Théophane Weber, Nicolas Heess, Lars Buesing +1
Stochastic computation graphs (SCGs) provide a formalism to represent structured optimization problems arising in artificial intelligence, including supervised, unsupervised, and r…
An investigation of model-free planning
Arthur Guez, Mehdi Mirza, Karol Gregor +10
The field of reinforcement learning (RL) is facing increasingly challenging domains with combinatorial complexity. For an RL agent to address these challenges, it is essential that…