Achieving a widely accepted definition of human intelligence has been challenging, a
situation mirrored by the diverse definitions of artificial intelligence in computer science. By …

The rapid advancement of chat-based language models has led to remarkable progress in
complex task-solving. However, their success heavily relies on human input to guide the …

Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …

Communication is an effective mechanism for coordinating the behaviors of multiple agents,
broadening their views of the environment, and to support their collaborations. In the field of …

Both Minsky's" society of mind" and Schmidhuber's" learning to think" inspire diverse
societies of large multimodal neural networks (NNs) that solve problems by interviewing …

High-performing teams learn effective communication strategies to judiciously share
information and reduce the cost of communication overhead. Within multi-agent …

High-performing teams learn intelligent and efficient communication and coordination
strategies to maximize their joint utility. These teams implicitly understand the different roles …

During dynamic social interaction, inferring and predicting others' behaviors through theory
of mind (ToM) is crucial for obtaining benefits in cooperative and competitive tasks. Current …

Communication plays a crucial role in information sharing within the field of multi-agent
reinforcement learning (MARL). However, how to transmit information that meets individual …

Communication-based multiagent reinforcement learning (MARL) has shown promising
results in promoting cooperation by enabling agents to exchange information. However, the …