Distributed Planning Algorithm for Coalition Logistics in Semi-trusted Environment

We present a collective approach to coalition logistics planning that presents the features crucial for application in an adversarial environment: planning and communication efficiency, well-defined levels of information to be shared, tight integration of trustfulness with the planning and stability with respect to imprecise trustfulness values. To achieve this goal, we combine multi-agent negotiation with efficient fuzzy and flexible linear programming techniques from operation research field. Alternating rounds of global optimization and restricted negotiation split the task into sub-tasks, create teams, assign them to the tasks and provide a task-resource mapping. Resulting plan execution can be easily verified and verification results can be used to update the trust and social models and potentially to perform re-planning immediately