6 papers
Learning Agile Striker Skills for Humanoid Soccer Robots from Noisy Sensory Input
Zifan Xu, Myoungkyu Seo, Dongmyeong Lee +8
Learning fast and robust ball-kicking skills is a critical capability for humanoid soccer robots, yet it remains a challenging problem due to the need for rapid leg swings, postura…
VGC-Bench: Towards Mastering Diverse Team Strategies in Competitive Pokémon
Cameron Angliss, Jiaxun Cui, Jiaheng Hu +2
Developing AI agents that can robustly adapt to varying strategic landscapes without retraining is a central challenge in multi-agent learning. Pokémon Video Game Championships (V…
Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
Chandler Smith, Marwa Abdulhai, Manfred Diaz +83
Large Language Model (LLM) agents have demonstrated impressive capabilities for social interaction and are increasingly being deployed in situations where they might engage with bo…
ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork
Caroline Wang, Arrasy Rahman, Jiaxun Cui +2
Learning to collaborate with previously unseen partners is a fundamental generalization challenge in multi-agent learning, known as Ad Hoc Teamwork (AHT). Existing AHT approaches o…
SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation
Michael J. Munje, Chen Tang, Shuijing Liu +6
Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit…
CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning
Jiaxun Cui, Chen Tang, Jarrett Holtz +4
Past work has demonstrated that autonomous vehicles can drive more safely if they communicate with each other. However, this communication is usually not human-understandable. Usin…