Abstract
How to form a team for achieving a given set of tasks is an important issue in multi-agent systems. Task-oriented team formation is the problem of selecting a group of agents, where each agent is characterized by a set of capabilities; the objective is to achieve a given set of tasks, where each task is made precise by a set of capabilities necessary for managing it. Robustness (i.e., the ability to reach the goal even if some agents break down) is an expected property of a team. In this paper, the focus is laid on the Task-Oriented Robust Team Formation (TORTF) problem. A formal framework is defined and some decision and optimization problems for TORTF are pointed out. The computational complexity of TORTF is then identified. Interestingly, TORTF does not prove more computationally demanding than the task-efficient team formation problem, i.e., robustness is in some sense "for free". In order to solve these TORTF problems, two algorithms, ART (Algorithm for Robust Team) for the decision problem and AORT (Algorithm for Optimal Robust Team) for bi-objective constraint optimization problems, are presented and evaluated on a number of benchmarks.
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