Dong Ki Kim

Learning Hierarchical Teaching Policies for Cooperative Agents

2019 · arXiv (Cornell University)

Collective learning can be greatly enhanced when agents effectively exchange knowledge with their peers. In particular, recent work studying agents that learn to teach other teammates has demonstrated that action advising accelerates team-wide learning. However, …

Context-Specific Representation Abstraction for Deep Option Learning

2021 · arXiv (Cornell University)

Hierarchical reinforcement learning has focused on discovering temporally extended actions, such as options, that can provide benefits in problems requiring extensive exploration. One promising approach that learns these options end-to-end is the option-critic (OC) framework. …

TOD-Flow: Modeling the Structure of Task-Oriented Dialogues

2023 · arXiv (Cornell University)

Task-Oriented Dialogue (TOD) systems have become crucial components in interactive artificial intelligence applications. While recent advances have capitalized on pre-trained language models (PLMs), they exhibit limitations regarding transparency and controllability. To address these challenges, we …