This demo illustrates MAS-DisCoSim 4 PDP, a testbed environment for evaluating distributed multi-agent system solutions to pickup and delivery problems (PDPs). PDPs are well-studi...
Jelle Van Gompel, Bart Tuts, Rutger Claes, Mario C...
Autonomous agents transcend their individual capabilities by cooperating towards achieving shared goals. The different viewpoints agents have on the environment cause disagreement...
Alexandros Belesiotis, Michael Rovatsos, Iyad Rahw...
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...
Most agent-based modeling techniques generate only a single trajectory in each run, greatly undersampling the space of possible trajectories. Swarming agents can explore a great m...
Social laws have proved to be a powerful and theoretically elegant framework for coordination in multi-agent systems. Most existing models of social laws assume that a designer is...
Games are used to evaluate and advance Multiagent and Artificial Intelligence techniques. Most of these games are deterministic with perfect information (e.g. Chess and Checkers)....
In typical multiagent teamwork settings, the teammates are either programmed together, or are otherwise provided with standard communication languages and coordination protocols. ...
We introduce a constrained mechanism design setting called internal implementation, in which the mechanism designer is explicitly modeled as a player in the game of interest. This...