Enlightened by the big success of pre-training in natural language
proce...
Preference-based Reinforcement Learning (PbRL) has demonstrated remarkab...
The emergence of large language models (LLMs) has substantially influenc...
Deployment of reinforcement learning algorithms for robotics application...
Cooperative multi-agent reinforcement learning (MARL) requires agents to...
Zero-shot human-AI coordination holds the promise of collaborating with
...
The booming development and huge market of micro-videos bring new e-comm...
Nonlinear dimensionality reduction lacks interpretability due to the abs...
Many real-world scenarios involve a team of agents that have to coordina...
The Elo rating system is widely adopted to evaluate the skills of (chess...
Deep reinforcement learning provides a promising approach for text-based...
In this paper, we propose a general meta learning approach to computing
...
Solving multi-goal reinforcement learning (RL) problems with sparse rewa...
It is a long-standing question to discover causal relations among a set ...
Reward shaping (RS) is a powerful method in reinforcement learning (RL) ...
We study reinforcement learning (RL) for text-based games, which are
int...
In many real-world problems, a team of agents need to collaborate to max...
Recent studies have highlighted that deep neural networks (DNNs) are
vul...