SOURCE-LINKED INTELLIGENCE

Control for Safety-Constrained Interactive Systems

CORDIS · observation · Publication date unknown

or ensuring safety and performance for multiagent stochastic dynamic games. Dynamic game theory provides a powerful foundation for addressing interactive decision-making problems. Recent advances in artificial intelligence, particularly in solving complex multiagent problems, have led to the development of scalable algorithms for such decision-making challenges. However, existing algorithms lack provable performance guarantees when applied to real-world systems with constraints, leaving a critical gap in the field. The proposed research program addresses this gap by developing a theoretical framework guided by real-world challenges. To achieve this, it proposes to integrate recent breakthroughs in three fundamental fields of stochastic control, game theory and learning theory: safety assurance and control under partial information from stochastic control, characterizing tractable classes of games and ensuring equilibrium efficiency from game theory, and powerful function approximators with provable guarantees from learning theory. To bridge theory and practice, the program ve

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recordType

award

status

SIGNED

region

EU

value

1989960

unit

EUR