Probably Approximately Correct Protocols for Reactive Control and Learning
Technical point of contact: Purush Iyer, ARO
Period of activity: 2015-2018
Overview of the Project
We partition the work into three research thrusts:
- Probably approximate correctness in joint learning and temporal logic-constrained reactive synthesis: How can we adapt the notions of probably approximate correctness for safety-critical systems operating in environments with both stochastic uncertainties and adversarial opponents subject to temporal logic specifications?
- Quantitative trade-offs, resilience and regret in joint learning and synthesis: How can we leverage the formalism from Thrust I to investigate exploration vs. exploration trade-offs, resilience of the joint protocols to changes between the design and deployment domains, and unconventional interactions between the controlled system and its environment and opponents?
- Applications in shared control: We put the interplay between learning and reactive control into a concrete context and demonstrate the utility of our results through a case study in which a human operator works with unmanned systems with various levels of autonomy capabilities.