44 citations · 66 across the 7 of their papers we have counts for
5 papers · 1 filter
Influencing Reinforcement Learning through Natural Language Guidance
Tasmia Tasrin, Md Sultan Al Nahian, Habarakadage Perera +1
Interactive reinforcement learning agents use human feedback or instruction to help them learn in complex environments. Often, this feedback comes in the form of a discrete signal…
Learning Norms from Stories: A Prior for Value Aligned Agents
Spencer Frazier, Md Sultan Al Nahian, Mark Riedl +1
Value alignment is a property of an intelligent agent indicating that it can only pursue goals and activities that are beneficial to humans. Traditional approaches to value alignme…
Monte-Carlo Tree Search for Simulation-based Strategy Analysis
Alexander Zook, Brent Harrison, Mark O. Riedl
Games are often designed to shape player behavior in a desired way; however, it can be unclear how design decisions affect the space of behaviors in a game. Designers usually explo…
Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptions
Upol Ehsan, Pradyumna Tambwekar, Larry Chan +2
Automated rationale generation is an approach for real-time explanation generation whereby a computational model learns to translate an autonomous agent's internal state and action…
Guiding Reinforcement Learning Exploration Using Natural Language
Brent Harrison, Upol Ehsan, Mark O. Riedl
In this work we present a technique to use natural language to help reinforcement learning generalize to unseen environments. This technique uses neural machine translation, specif…