Junhyuk Oh | DeepAI

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∙ 10/25/2022

In-context Reinforcement Learning with Algorithm Distillation

We propose Algorithm Distillation (AD), a method for distilling reinforc...

1 Michael (Misha) Laskin, et al. ∙

∙ 10/08/2021

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Strategic diversity is often essential in games: in multi-player games, ...

0 Marta Garnelo, et al. ∙

∙ 02/12/2021

Discovery of Options via Meta-Learned Subgoals

Temporal abstractions in the form of options have been shown to help rei...

5 Vivek Veeriah, et al. ∙

∙ 10/13/2020

Balancing Constraints and Rewards with Meta-Gradient D4PG

Deploying Reinforcement Learning (RL) agents to solve real-world applica...

0 Dan A. Calian, et al. ∙

∙ 07/17/2020

Discovering Reinforcement Learning Algorithms

Reinforcement learning (RL) algorithms update an agent's parameters acco...

72 Junhyuk Oh, et al. ∙

∙ 07/16/2020

Meta-Gradient Reinforcement Learning with an Objective Discovered Online

Deep reinforcement learning includes a broad family of algorithms that p...

9 Zhongwen Xu, et al. ∙

∙ 12/11/2019

What Can Learned Intrinsic Rewards Capture?

Reinforcement learning agents can include different components, such as ...

25 Zeyu Zheng, et al. ∙

∙ 09/10/2019

Discovery of Useful Questions as Auxiliary Tasks

Arguably, intelligent agents ought to be able to discover their own ques...

7 Vivek Veeriah, et al. ∙

∙ 12/03/2018

Generative Adversarial Self-Imitation Learning

This paper explores a simple regularizer for reinforcement learning by p...

0 Yijie Guo, et al. ∙

∙ 11/05/2018

Contingency-Aware Exploration in Reinforcement Learning

This paper investigates whether learning contingency-awareness and contr...

8 Jongwook Choi, et al. ∙

∙ 07/19/2018

Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies

We introduce a new RL problem where the agent is required to execute a g...

0 Sungryull Sohn, et al. ∙

∙ 06/22/2018

Many-Goals Reinforcement Learning

All-goals updating exploits the off-policy nature of Q-learning to updat...

0 Vivek Veeriah, et al. ∙

∙ 06/14/2018

Self-Imitation Learning

This paper proposes Self-Imitation Learning (SIL), a simple off-policy a...

0 Junhyuk Oh, et al. ∙

∙ 04/17/2018

On Learning Intrinsic Rewards for Policy Gradient Methods

In many sequential decision making tasks, it is challenging to design re...

0 Zeyu Zheng, et al. ∙

∙ 02/22/2018

Unicorn: Continual Learning with a Universal, Off-policy Agent

Some real-world domains are best characterized as a single task, but for...

0 Daniel J. Mankowitz, et al. ∙

∙ 07/11/2017

Value Prediction Network

This paper proposes a novel deep reinforcement learning (RL) architectur...

0 Junhyuk Oh, et al. ∙

∙ 06/15/2017

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning

As a step towards developing zero-shot task generalization capabilities ...

0 Junhyuk Oh, et al. ∙

∙ 05/30/2016

Control of Memory, Active Perception, and Action in Minecraft

In this paper, we introduce a new set of reinforcement learning (RL) tas...

0 Junhyuk Oh, et al. ∙

∙ 12/24/2015

Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network

We propose a novel weakly-supervised semantic segmentation algorithm bas...

0 Seunghoon Hong, et al. ∙

∙ 07/31/2015

Action-Conditional Video Prediction using Deep Networks in Atari Games

Motivated by vision-based reinforcement learning (RL) problems, in parti...

0 Junhyuk Oh, et al. ∙

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