Reinforcement Learning-Based Coverage Path Planning with Implicit Cellular Decomposition

no code implementations • 18 Oct 2021 • Javad Heydari, Olimpiya Saha, Viswanath Ganapathy

In this paper, we provide a systematic analysis of the coverage problem and formulate it as an optimal stopping time problem, where the trade-off between coverage performance and its cost is explicitly accounted for.

reinforcement-learning Reinforcement Learning (RL)

A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it

no code implementations • 11 Oct 2021 • Viswanath Ganapathy, Sauptik Dhar, Olimpiya Saha, Pelin Kurt Garberson, Javad Heydari, Mohak Shah

In recent times, advances in artificial intelligence (AI) and IoT have enabled seamless and viable maintenance of appliances in home and building environments.

Anomaly Detection

Universum GANs: Improving GANs through contradictions

no code implementations • 18 Jun 2021 • Sauptik Dhar, Javad Heydari, Samarth Tripathi, Unmesh Kurup, Mohak Shah

Limited availability of labeled-data makes any supervised learning problem challenging.

Synthetic Data Generation