4 papers
Reasoning with Scene Graphs for Robot Planning under Partial Observability
Saeid Amiri, Kishan Chandan, Shiqi Zhang
Robot planning in partially observable domains is difficult, because a robot needs to estimate the current state and plan actions at the same time. When the domain includes many ob…
Guiding Robot Exploration in Reinforcement Learning via Automated Planning
Yohei Hayamizu, Saeid Amiri, Kishan Chandan +2
Reinforcement learning (RL) enables an agent to learn from trial-and-error experiences toward achieving long-term goals; automated planning aims to compute plans for accomplishing…
Augmenting Knowledge through Statistical, Goal-oriented Human-Robot Dialog
Saeid Amiri, Sujay Bajracharya, Cihangir Goktolga +2
Some robots can interact with humans using natural language, and identify service requests through human-robot dialog. However, few robots are able to improve their language capabi…
Learning and Reasoning for Robot Sequential Decision Making under Uncertainty
Saeid Amiri, Mohammad Shokrolah Shirazi, Shiqi Zhang
Robots frequently face complex tasks that require more than one action, where sequential decision-making (SDM) capabilities become necessary. The key contribution of this work is a…