Project Grant 2312342

Award Date 8/1/23
Completion Date 7/31/26
Dollars Obligated $855K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Pittsburgh, PA 15213, USA
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  1. Scalable subtree solving algorithms for imperfect-information extensive-form strategic settings.
  2. Scalable subtree solving techniques when the computational requirements of the common knowledge closure are too large.
  3. Techniques to find equilibrium strategies in strategic settings where the rules are not provided and the solver only has access to a simulator.

The research will enable more realistic and scalable modeling of strategic interactions across a wide range of real-world applications, including negotiation, business, defense, cybersecurity, and more. The results will be incorporated into new CMU courses on computational game solving and cooperative AI, as well as the university's undergraduate and graduate AI curriculum.

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