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Planning Technology Solves Rescue Missions

New Danish research into search algorithms can solve complex planning problems in rescue missions in association with natural catastrophes and military operations. Associate Professor Rune Moeller Jensen from the IT University of Copenhagen has received recognition for combining two different principles within computer science which can be used to rapidly develop emergency plans which take into consideration unforeseen events.

Rune Moeller Jensen is researching automatic planning at The IT University of Copenhagen. "Planning is based on selecting and organizing activities in relation to their expected outcome to achieve specific goals. We all know planning problems from everyday life. If we, for example, are building a house, there are many activities which need to be coordinated. Such as the house's foundation needs to be completed before the walls can be built", explains Rune Moeller Jensen, adding that the same applies within IT.

"Planning technology has progressed a very long way and the number of industrial applications is increasing rapidly", says Rune Moeller Jensen. Automatic planning is used for example in air traffic control and in the planning of military rescue operations.

Automatic planning is part of an area within computer science called artificial intelligence. The goal is to develop algorithms which use descriptions of planning problems, such as a rescue operation, to return a plan of how such complex situations can be solved. Automatic planning is very challenging. "If, for example, there are 25 different things you could bring with you in a rescue helicopter such as oxygen masks, resuscitation equipment and life jackets, then there are in general 225 or more than 33 million ways to load the helicopter", explains Rune Moeller Jensen.

New Efficient Combination Creates New Opportunities

Rune Moeller Jensen’s research can be seen as providing a way to combine route planning principles with principles for automatic fault finding. "My research has combined two different but complementary principles for handling complex planning problems, developed within the computer science disciplines of artificial intelligence and formal verification", explains Rune Moeller Jensen.

Several research groups have tried to combine the two principles. However, this has been shown to be difficult. Rune Moeller Jensen has, in co-operation with American colleagues from Carnegie Mellon University, developed a method called state-set-branching, in which the two principles can be combined. "We could show that these search algorithms were more efficient than previous algorithms", he says. He explains that the new technology has been used to plan search and rescue operations for the American air force.

Pia Svejgaard Pedersen | alfa
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