This competition aims to motivate work in the broad field of multi-agent systems and logistics. We have prepared a benchmarking framework which allows the development of multi-agent swarms to process a variety of test environments. Those can be extremely diverse, dynamic and variable of size. The ultimate goal of this competition is to foster comparability of multi-agent systems in logistics-related problems (e. g., in hospital logistics). Many such problems have good accessibility and are easy to comprehend, but hard to solve. Problems of different diffculty have been designed to make the framework interesting for educational purposes. However, finding effcient solutions for different a priori unknown test environments remains a challenging task for practitioners and researchers alike.
Following these ideas, in the AbstractSwarm Multi-Agent Logistics Competition, participants must develop agents that are able to cooperatively solve different a priori unknown logistics problems. A logistics problem is given as a graph containing agents and stations. An agent can interact with the graph (1) by deciding which station to visit next, (2) by communicating with other agents, and (3) by retrieving a reward for its previous decision. While simulating a scenario, a timetable in the form of a Gantt-chart is created according to the decisions of all agents. Submissions will be ranked according to the total number of idle time of all agents in several different a priori unknown problem scenarios in conjunction with the number of iterations needed to come to the solution.