Visitors
Sitemap
Every page on the site. There is also an [XML sitemap](https://lening.li/sitemap.xml) for crawlers.Pages
Lening Li (郦乐宁)
Robotics engineer and researcher — reinforcement learning, optimal control, game theory, and formal methods.
research
Anytime Planning via Function Approximation and Importance Sampling
Planning for nonlinear robotic systems is NP-complete, so approximate schemes — discretization-based (A*) and sampling-based (RRT*) — dominate practice. We explore a third approach: function approximation, which transforms planning in the state space into planning in a low-dimensional parameter space of policy function approximators.
DARPA Robotics Challenge
Formal Methods and Game Theory for Cyber-Physical Security
In an adversarial environment, information — and the lack of it — is decisive for strategic decision-making. We developed a class of hypergames on graphs to model the interaction between an intelligent robot and its adversary when the task is given in temporal logic and the two players hold asymmetric information.
Learning-based Planning with Temporal Logic Constraints
The goal is a model-free reinforcement learning method for stochastic planning under temporal logic constraints — so that a robot can be given a high-level task and return a policy that provably satisfies it.