14 citations · 42 across the 10 of their papers we have counts for
18 papers
LOA: Logical Optimal Actions for Text-based Interaction Games
Daiki Kimura, Subhajit Chaudhury, Masaki Ono +6
We present Logical Optimal Actions (LOA), an action decision architecture of reinforcement learning applications with a neuro-symbolic framework which is a combination of neural ne…
Neuro-Symbolic Reinforcement Learning with First-Order Logic
Daiki Kimura, Masaki Ono, Subhajit Chaudhury +6
Deep reinforcement learning (RL) methods often require many trials before convergence, and no direct interpretability of trained policies is provided. In order to achieve fast conv…
Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agents
Keerthiram Murugesan, Subhajit Chaudhury, Kartik Talamadupula
Text-based games (TBGs) have become a popular proving ground for the demonstration of learning-based agents that make decisions in quasi real-world settings. The crux of the proble…
Reinforcement Learning with External Knowledge by using Logical Neural Networks
Daiki Kimura, Subhajit Chaudhury, Akifumi Wachi +4
Conventional deep reinforcement learning methods are sample-inefficient and usually require a large number of training trials before convergence. Since such methods operate on an u…
Image inpainting using frequency domain priors
Hiya Roy, Subhajit Chaudhury, Toshihiko Yamasaki +1
In this paper, we present a novel image inpainting technique using frequency domain information. Prior works on image inpainting predict the missing pixels by training neural netwo…
VisualHints: A Visual-Lingual Environment for Multimodal Reinforcement Learning
Thomas Carta, Subhajit Chaudhury, Kartik Talamadupula +1
We present VisualHints, a novel environment for multimodal reinforcement learning (RL) involving text-based interactions along with visual hints (obtained from the environment). Re…