Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
The Aero Repair and Overhaul industry is facing an increasing challenge of prediction and scheduling of engine overhauls to remain competitive in a complex business arena. An appr...
Armin Stranjak, Partha Sarathi Dutta, Mark Ebden, ...
Two currently active strands of research on logics for multi-agent systems are dynamic epistemic logic, focusing on the epistemic consequences of actions, and logics of coalitiona...
Background: Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this ...
Faheem Mitha, Timothy A. Lucas, Feng Feng, Thomas ...
Existing task allocation algorithms generally do not consider the effects of task interaction, such as interference, but instead assume that tasks are independent. That assumptio...