12 citations · 16 across the 4 of their papers we have counts for
4 papers
Optimal Control of Partially Observable Markov Decision Processes with Finite Linear Temporal Logic Constraints
Krishna C. Kalagarla, Dhruva Kartik, Dongming Shen +3
Autonomous agents often operate in scenarios where the state is partially observed. In addition to maximizing their cumulative reward, agents must execute complex tasks with rich t…
Model-Free Reinforcement Learning for Optimal Control of MarkovDecision Processes Under Signal Temporal Logic Specifications
Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo
We present a model-free reinforcement learning algorithm to find an optimal policy for a finite-horizon Markov decision process while guaranteeing a desired lower bound on the prob…
Synthesis of Discounted-Reward Optimal Policies for Markov Decision Processes Under Linear Temporal Logic Specifications
Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo
We present a method to find an optimal policy with respect to a reward function for a discounted Markov decision process under general linear temporal logic (LTL) specifications. P…
A Sample-Efficient Algorithm for Episodic Finite-Horizon MDP with Constraints
Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo
Constrained Markov Decision Processes (CMDPs) formalize sequential decision-making problems whose objective is to minimize a cost function while satisfying constraints on various c…