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Resilient Strategies for Stochastic Systems: How Much Does It Take to Break a Winning Strategy?
arXiv – CS AI|Kush Grover, Markel Zubia, Debraj Chakraborty, Muqsit Azeem, Nils Jansen, Jan Kretinsky||1 views
🤖AI Summary
Researchers introduce resilient strategies for stochastic systems, focusing on decision-making that remains robust against disturbances that could flip agent decisions. The work presents fundamental problems for Markov decision processes with reachability and safety objectives, extending to stochastic games with various disturbance aggregation methods.
Key Takeaways
- →New concept of resilience introduced for stochastic decision-making systems under uncertainty.
- →Framework addresses disturbances that can flip agent decisions, such as actuator malfunctions.
- →Research covers Markov decision processes with reachability and safety objectives.
- →Multiple methods provided for aggregating disturbance amounts including expectation and worst-case scenarios.
- →Quantitative measures introduced to handle infinite disturbances through frequency analysis.
#stochastic-systems#markov-decision-processes#resilient-strategies#robustness#ai-research#decision-making#uncertainty#game-theory
Read Original →via arXiv – CS AI
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