Multi-agent planning for mixed human-robot environments faces significant challenges. Current methodologies, which often rely on data-driven human motion prediction and ...
LyzrCore presents Lyzr Automatawhich represents a significant advancement in the field of process automation, offering a low-code multi-agent framework designed ...
Information retrieval and integration are critical processes that underpin analysis and decision making in a variety of fields. These processes ...
The problem of a mediator learning to coordinate a group of strategic agents is posed through recommendations of actions without ...
In the last decade, the data-driven method using deep neural networks has boosted the success of ai in various challenging ...
The emergence of large language models (LLMs) has markedly improved the domain of computational linguistics, particularly in multi-agent systems. Despite ...
