The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.Personnel recovery teams must operate under intense pressure, taking into account not\ud only hard logistics, but ‘messy’ factors such as the social or political implications of a decision. The Collaborative Operations for Personnel Recovery (Co-OPR) project has\ud developed decision-support for sensemaking in such scenarios, seeking to exploit the\ud complementary strengths of human and machine reasoning. Co-OPR integrates the Compendium sensemaking-support tool for real time information and argument mapping, with the I-X artificial intelligence planning and execution framework to support group activity and collaboration. Both share a common model for dealing with issues, the refinement of options for the activities to be performed, handling constraints and recording other information. The tools span the spectrum from being very flexible with few constraints on terminology and content, to knowledge-based relying on rich domain models and formal conceptual models (ontologies). In a personnel recovery experimental simulation of an UN peacekeeping operation, with roles played by military planning staff, the Co-OPR tools were judged by external evaluators to have been very effective
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.