Embodied Artificial Intelligence (Embodied AI) is crucial for achieving Artificial General
Intelligence (AGI) and serves as a foundation for various applications that bridge cyberspace …

Diplomacy is one of the most sophisticated activities in human society, involving complex
interactions among multiple parties that require skills in social reasoning, negotiation, and …

With the emergence of large language models (LLMs), LLM-powered multi-agent systems
(LLM-MA systems) have been proposed to tackle real-world tasks. However, their agents …

Large Language Models (LLMs) are powerful tools with the potential to benefit society
immensely, yet, they have demonstrated biases that perpetuate societal inequalities …

The rapid evolution of large language models (LLMs) and their capacity to simulate human
cognition and behavior has given rise to LLM-based frameworks and tools that are …

The rise of unifying frameworks that enable seamless interoperability of Large Language
Models (LLMs) has made LLM-LLM collaboration for open-ended tasks a possibility. Despite …

Learning a world model for model-free Reinforcement Learning (RL) agents can significantly
improve the sample efficiency by learning policies in imagination. However, building a world …

Traditional sociological research often relies on human participation, which, though
effective, is expensive, challenging to scale, and with ethical concerns. Recent …

The cooperative driving technology of Connected and Autonomous Vehicles (CAVs) is
crucial for improving the efficiency and safety of transportation systems. Learning-based …

Multi-agent reinforcement learning is a key method for training multi-robot systems over a
series of episodes in which robots are rewarded or punished according to their performance; …