Summary of Simulating User Agents For Embodied Conversational-ai, by Daniel Philipov et al.
Simulating User Agents for Embodied Conversational-AIby Daniel Philipov, Vardhan Dongre, Gokhan Tur, Dilek Hakkani-TürFirst submitted…
Simulating User Agents for Embodied Conversational-AIby Daniel Philipov, Vardhan Dongre, Gokhan Tur, Dilek Hakkani-TürFirst submitted…
Predicting Future Actions of Reinforcement Learning Agentsby Stephen Chung, Scott Niekum, David KruegerFirst submitted to…
From Silos to Systems: Process-Oriented Hazard Analysis for AI Systemsby Shalaleh Rismani, Roel Dobbe, AJung…
Self-Driving Car Racing: Application of Deep Reinforcement Learningby Florentiana Yuwono, Gan Pang Yen, Jason ChristopherFirst…
Active Legibility in Multiagent Reinforcement Learningby Yanyu Liu, Yinghui Pan, Yifeng Zeng, Biyang Ma, Doshi…
Offline-to-Online Multi-Agent Reinforcement Learning with Offline Value Function Memory and Sequential Explorationby Hai Zhong, Xun…
Shared Control with Black Box Agents using Oracle Queriesby Inbal Avraham, Reuth MirskyFirst submitted to…
Multi-agent cooperation through learning-aware policy gradientsby Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer,…
Towards Visual Text Design Transfer Across Languagesby Yejin Choi, Jiwan Chung, Sumin Shim, Giyeong Oh,…
Cross-lingual Transfer of Reward Models in Multilingual Alignmentby Jiwoo Hong, Noah Lee, Rodrigo Martínez-Castaño, César…