1 citations · 3 across the 6 of their papers we have counts for
6 papers
A Framework for Learning Scoring Rules in Autonomous Driving Planning Systems
Zikang Xiong, Joe Kurian Eappen, Suresh Jagannathan
In autonomous driving systems, motion planning is commonly implemented as a two-stage process: first, a trajectory proposer generates multiple candidate trajectories, then a scorin…
Scaling Safe Multi-Agent Control for Signal Temporal Logic Specifications
Joe Eappen, Zikang Xiong, Dipam Patel +2
Existing methods for safe multi-agent control using logic specifications like Signal Temporal Logic (STL) often face scalability issues. This is because they rely either on single-…
Derivative-Guided Symbolic Execution
Yongwei Yuan, Zhe Zhou, Julia Belyakova +1
We consider the formulation of a symbolic execution (SE) procedure for functional programs that interact with effectful, opaque libraries. Our procedure allows specifications of li…
Manipulating Neural Path Planners via Slight Perturbations
Zikang Xiong, Suresh Jagannathan
Data-driven neural path planners are attracting increasing interest in the robotics community. However, their neural network components typically come as black boxes, obscuring the…
Morpheus: Automated Safety Verification of Data-dependent Parser Combinator Programs
Ashish Mishra, Suresh Jagannathan
Parser combinators are a well-known mechanism used for the compositional construction of parsers, and have shown to be particularly useful in writing parsers for rich grammars with…
DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems
Joe Eappen, Suresh Jagannathan
While notable progress has been made in specifying and learning objectives for general cyber-physical systems, applying these methods to distributed multi-agent systems still pose…