research
∙
02/28/2023
Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments
Learning to detect, characterize and accommodate novelties is a challeng...
share
research
∙
02/17/2023
Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning
Preference Based Reinforcement Learning has shown much promise for utili...
research
∙
02/17/2023
A State Augmentation based approach to Reinforcement Learning from Human Preferences
Reinforcement Learning has suffered from poor reward specification, and ...
research
∙
02/17/2023
Data Driven Reward Initialization for Preference based Reinforcement Learning
Preference-based Reinforcement Learning (PbRL) methods utilize binary fe...
research
∙
10/17/2022
Symbol Guided Hindsight Priors for Reward Learning from Human Preferences
Specifying rewards for reinforcement learned (RL) agents is challenging....
research
∙
10/07/2022
Advice Conformance Verification by Reinforcement Learning agents for Human-in-the-Loop
Human-in-the-loop (HiL) reinforcement learning is gaining traction in do...
research
∙
09/15/2021
Synthesizing Policies That Account For Human Execution Errors Caused By State-Aliasing In Markov Decision Processes
When humans are given a policy to execute, there can be policy execution...
research
∙
05/03/2021
Trust-Aware Planning: Modeling Trust Evolution in Longitudinal Human-Robot Interaction
Trust between team members is an essential requirement for any successfu...
research
∙
07/12/2020
Fine-grained Language Identification with Multilingual CapsNet Model
Due to a drastic improvement in the quality of internet services worldwi...
research
∙
02/04/2020
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Black Box Simulators
As more and more complex AI systems are introduced into our day-to-day l...
research
∙
12/06/2019
