29 citations · 80 across the 11 of their papers we have counts for
12 papers
Augmentations for Robust and Efficient Imitation Learning in Streamed Video Games
Somjit Nath, Abdelhak Lemkhenter, Pallavi Choudhury +4
Imitation learning is an appealing way to scale game-playing agents to complex 3D environments by training policies to map visual observations to actions from human demonstrations.…
When Does Predictive Inverse Dynamics Outperform Behavior Cloning?
Lukas Schäfer, Pallavi Choudhury, Abdelhak Lemkhenter +10
Behavior cloning (BC) is a practical offline imitation learning method, but it often fails when expert demonstrations are limited. Recent works have introduced a class of architect…
Adapting a World Model for Trajectory Following in a 3D Game
Marko Tot, Shu Ishida, Abdelhak Lemkhenter +10
Imitation learning is a powerful tool for training agents by leveraging expert knowledge, and being able to replicate a given trajectory is an integral part of it. In complex envir…
Imitating Human Behaviour with Diffusion Models
Tim Pearce, Tabish Rashid, Anssi Kanervisto +8
Diffusion models have emerged as powerful generative models in the text-to-image domain. This paper studies their application as observation-to-action models for imitating human be…
Fully Distributed Actor-Critic Architecture for Multitask Deep Reinforcement Learning
Sergio Valcarcel Macua, Ian Davies, Aleksi Tukiainen +1
We propose a fully distributed actor-critic architecture, named Diff-DAC, with application to multitask reinforcement learning (MRL). During the learning process, agents communicat…
Compatible features for Monotonic Policy Improvement
Marcin B. Tomczak, Sergio Valcarcel Macua, Enrique Munoz de Cote +1
Recent policy optimization approaches have achieved substantial empirical success by constructing surrogate optimization objectives. The Approximate Policy Iteration objective (Sch…