DeepAI AI Chat
Log In Sign Up

Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes

by   Maxime Bouton, et al.

Autonomous systems are often required to operate in partially observable environments. They must reliably execute a specified objective even with incomplete information about the state of the environment. We propose a methodology to synthesize policies that satisfy a linear temporal logic formula in a partially observable Markov decision process (POMDP). By formulating a planning problem, we show how to use point-based value iteration methods to efficiently approximate the maximum probability of satisfying a desired logical formula and compute the associated belief state policy. We demonstrate that our method scales to large POMDP domains and provides strong bounds on the performance of the resulting policy.


page 1

page 2

page 3

page 4


Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method

There is much interest in using partially observable Markov decision pro...

Improving Training Result of Partially Observable Markov Decision Process by Filtering Beliefs

In this study I proposed a filtering beliefs method for improving perfor...

Model-free Motion Planning of Autonomous Agents for Complex Tasks in Partially Observable Environments

Motion planning of autonomous agents in partially known environments wit...

Technical Report: Distribution Temporal Logic: Combining Correctness with Quality of Estimation

We present a new temporal logic called Distribution Temporal Logic (DTL)...

Technical Report: The Policy Graph Improvement Algorithm

Optimizing a partially observable Markov decision process (POMDP) policy...

Planning under periodic observations: bounds and bounding-based solutions

We study planning problems faced by robots operating in uncertain enviro...

Reinforcement Learning with Temporal Logic Constraints for Partially-Observable Markov Decision Processes

This paper proposes a reinforcement learning method for controller synth...