Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel

Universally Expressive Communication in Multi-Agent Reinforcement Learning

Universally Expressive Communication in Multi-Agent Reinforcement Learning

Poster presented at the Deep Learning Indaba 2022 by Matthew Morris

Emergent Communication in Multi-Agent Reinforcement Learning for Flying Base Stations

EmoRL: Continuous Acoustic Emotion Classification using Deep Reinforcement Learning

Acoustically expressed emotions can make communication with a robot more efficient. Detecting emotio

Improved ASR for Under-Resourced Languages Through Multi-Task Learning with Acoustic Landmarks

Furui first demonstrated that the identity of both consonant and vowel can be perceived from the C-V

Towards a multi-agent model to prevent damage caused by cocoa mirids to cocoa pods

Co-localisées avec la Plate-Forme Intelligence Artificielle (PFIA 2019) International audience

Past to Present: Reassessing Evaluation in Multi-Agent Reinforcement Learning

Past to Present: Reassessing Evaluation in Multi-Agent Reinforcement Learning

Poster presented at the Deep Learning Indaba 2023 by Siddarth Singh