Distributed plan construction and execution for medical image interpretation

Research in the field of medical image interpretation inspired a multi-agent planning model in which a population of agents reaches global goals pursuing local plans and producing partial results. Cooperation is achieved by collecting results, reanalysing the reached state and starting new plans; local plans are generated and executed in a distributed way. The state is composed of a directed graph, describing the currently obtained results and of an attributed string, concatenating the trace of the performed operations with the current plan. A model of agent and agent generation is presented and an example of application given in the field of liver biopsy interpretation.