3 citations · 3 across the 4 of their papers we have counts for
5 papers
Reinforcement Learning with Complex (valued) Memories
Sathya Kamesh Bhethanabhotla, Efstratios Gavves, André Biedenkapp
Partially observable environments pose a fundamental challenge in deep reinforcement learning, requiring agents to compress temporal information from observations and maintain a me…
From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models
Christian Gumbsch, Leonardo Barcellona, Lennard Schünemann +7
Reinforcement learning relies on accurate reward functions, which are often hand-crafted or even unavailable in real-world applications, such as robotics. Recent work has explored…
Foundation Models in Robotics: A Comprehensive Review of Methods, Models, Datasets, Challenges and Future Research Directions
Aggelos Psiris, Vasileios Argyriou, Evangelos K. Markakis +5
Over the recent years, the field of robotics has been undergoing a transformative paradigm shift from fixed, single-task, domain-specific solutions towards adaptive, multi-function…
Reliably Re-Acting to Partner's Actions with the Social Intrinsic Motivation of Transfer Empowerment
Tessa van der Heiden, Herke van Hoof, Efstratios Gavves +1
We consider multi-agent reinforcement learning (MARL) for cooperative communication and coordination tasks. MARL agents can be brittle because they can overfit their training partn…
Robust Multi-Agent Reinforcement Learning with Social Empowerment for Coordination and Communication
T. van der Heiden, C. Salge, E. Gavves +1
We consider the problem of robust multi-agent reinforcement learning (MARL) for cooperative communication and coordination tasks. MARL agents, mainly those trained in a centralized…