Recent decades have seen a rise in the use of physics methods to study different societal
phenomena. This development has been due to physicists venturing outside of their …

A disease is an abnormal condition that negatively impacts the functioning of the human
body. Pathology determines the causes behind the disease and identifies its development …

Abstract We introduce the Multi-Agent Tracking Environment (MATE), a novel multi-agent
environment simulates the target coverage control problems in the real world. MATE hosts …

Collaborative vehicle routing occurs when carriers collaborate through sharing their
transportation requests and performing transportation requests on behalf of each other. This …

Collaborative Vehicle Routing is where delivery companies cooperate by sharing their
delivery information and performing delivery requests on behalf of each other. This achieves …

For tasks intractable for a single agent, agents must cooperate to accomplish complex goals.
A good example is coalitional games, where a group of individuals forms coalitions to …

The input vocabulary and the representations learned are crucial to the performance of
neural NLP models. Using the full vocabulary results in less explainable and more memory …

In the recent shift towards human-centric AI, the need for machines to accurately use natural
language has become increasingly important. While a common approach to achieve this is …

A core question in multi-agent systems is understanding the motivations for an agent's
actions based on their behavior. Inverse reinforcement learning provides a framework for …

We show how solution concepts from cooperative game theory can be used to tackle the
problem of pruning neural networks. The ever-growing size of deep neural networks (DNNs) …