Expected Impact:
The outcomes should contribute to:
- Reduce dependencies on non-European suppliers by boosting the EDTIB and promoting the development of a European solution.
- Faster and better planning and decision making (with less personnel) during mission planning and execution, resulting in higher mission success.
- Leverage Reinforcement Learning towards largely automating the modelling and implementation of expert-level (or beyond) competent battlespace agents, thereby greatly reducing the time and cost of course of action (COA) development and wargaming.
- Deliver a proof-of-concept demonstrator at least of TRL 5.
- Increase the opportunities for various smaller actors, including those not previously active in the defence sector, to adapt and apply innovative simulation technologies for defence applications.
- Increase business opportunities in the defence sector for EU and Associated Countries companies and promote technological edge in the field.
- Increasing the interoperability between EU armed forces and with NATO Allies.
- Increase opportunities and future involvement for third parties participating in FSTP in the field of simulation and training within tasks described previously in the call text under "Conditions related to FSTP".
Mission planning and execution in the present and future multi-domain operation environment (MDO) employing manned and unmanned force elements demand that the human decision makers are very well supported to be able to handle the complexity
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