Artificial intelligence in decision support modellingOpen date: Tuesday 25 September 2018 Close date: Monday 15 October 2018
Combat modelling and wargaming are some of the tools used by the Ministry of Defence (MoD) to assess the UK’s capabilities against perceived threats in plausible operational scenarios.
These tools are a vital support to UK Defence decision makers, the outputs provided are used to test and understand how effective different decisions can be.
Most of MOD’s current combat modelling techniques however either represent command decisions through simple rules-based systems or rely heavily on human users to provide the command context, whilst simulation handles the complex conclusions of the outcome.
These systems often require great physical effort to run and only consider a limited set of scenarios, resulting in significant uncertainty regarding outcomes.
As part of ongoing work looking at developing a new suite of capabilities that both reduce the manpower needed to make credible command decisions and enable the simulations to consider a wider range of situations, Defence Science and Technology Laboratory (Dstl) is seeking to understand how AI can be applied to support this mission.
Through developing these new innovative methods, Dstl is looking to:
Why you should get involved?
This is an opportunity for industry and academia to work with Dstl to help shape future models and improve current ones.
Through this event we hope to collaborate with industry and research partners to identify ideas for creating future simulations and models which can be applied widely and are cheaper to both operate and sustain.
Successful proposals submitted after the event may lead to Dstl funding contracts with collaborators with up to £400k to further explore and develop their ideas.
Who should apply?
We want to hear from innovators with a track record of developing deployable solutions with expertise in all or some of the following areas:
Companies with expertise in these technologies for non-defence applications are encouraged to apply.
The issues facing models and simulations are often highly complex, with multiple competing variables and goal constraints and the data needed to train AI system might be limited. Therefore, proposals which allow AI systems to operate credibly in a ‘small data’ situation are highly desirable.
Dstl models and simulations are used to support evidence-based decision making at all levels and as such should be as transparent as possible.