Vivek Veeriah | DeepAI

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∙ 08/17/2023

Diversifying AI: Towards Creative Chess with AlphaZero

In recent years, Artificial Intelligence (AI) systems have surpassed hum...

0 Tom Zahavy, et al. ∙

∙ 02/08/2022

GrASP: Gradient-Based Affordance Selection for Planning

Planning with a learned model is arguably a key component of intelligenc...

0 Vivek Veeriah, 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. ∙

∙ 02/09/2021

Learning State Representations from Random Deep Action-conditional Predictions

In this work, we study auxiliary prediction tasks defined by temporal-di...

0 Zeyu Zheng, et al. ∙

∙ 07/09/2020

Learning Retrospective Knowledge with Reverse Reinforcement Learning

We present a Reverse Reinforcement Learning (Reverse RL) approach for re...

25 Shangtong Zhang, et al. ∙

∙ 02/28/2020

Self-Tuning Deep Reinforcement Learning

Reinforcement learning (RL) algorithms often require expensive manual or...

20 Tom Zahavy, et al. ∙

∙ 12/15/2019

How Should an Agent Practice?

We present a method for learning intrinsic reward functions to drive the...

17 Janarthanan Rajendran, 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. ∙

∙ 03/08/2019

Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning

There is a long history of using meta learning as representation learnin...

0 Alex Kearney, 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. ∙

∙ 04/10/2018

TIDBD: Adapting Temporal-difference Step-sizes Through Stochastic Meta-descent

In this paper, we introduce a method for adapting the step-sizes of temp...

0 Alex Kearney, et al. ∙

∙ 12/09/2016

Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks

Representations are fundamental to artificial intelligence. The performa...

0 Vivek Veeriah, et al. ∙

∙ 06/09/2016

Face valuing: Training user interfaces with facial expressions and reinforcement learning

An important application of interactive machine learning is extending or...

0 Vivek Veeriah, et al. ∙

∙ 04/25/2015

Differential Recurrent Neural Networks for Action Recognition

The long short-term memory (LSTM) neural network is capable of processin...

0 Vivek Veeriah, et al. ∙

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