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07/17/2023
Image-based Regularization for Action Smoothness in Autonomous Miniature Racing Car with Deep Reinforcement Learning
Deep reinforcement learning has achieved significant results in low-leve...
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04/20/2023
Reinforcement Learning for Picking Cluttered General Objects with Dense Object Descriptors
Picking cluttered general objects is a challenging task due to the compl...
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04/18/2023
Learning Sim-to-Real Dense Object Descriptors for Robotic Manipulation
It is crucial to address the following issues for ubiquitous robotics ma...
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12/22/2022
A Local-Pattern Related Look-Up Table
This paper describes a Relevance-Zone pattern table (RZT) that can be us...
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11/07/2022
Are AlphaZero-like Agents Robust to Adversarial Perturbations?
The success of AlphaZero (AZ) has demonstrated that neural-network-based...
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05/19/2022
Image-Based Conditioning for Action Policy Smoothness in Autonomous Miniature Car Racing with Reinforcement Learning
In recent years, deep reinforcement learning has achieved significant re...
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12/05/2021
A Novel Approach to Solving Goal-Achieving Problems for Board Games
Goal-achieving problems are puzzles that set up a specific situation wit...
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11/22/2021
Optimistic Temporal Difference Learning for 2048
Temporal difference (TD) learning and its variants, such as multistage T...
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10/26/2021
Hinge Policy Optimization: Rethinking Policy Improvement and Reinterpreting PPO
Policy optimization is a fundamental principle for designing reinforceme...
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10/03/2021
An Unsupervised Video Game Playstyle Metric via State Discretization
On playing video games, different players usually have their own playsty...
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12/14/2020
Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search
Monte Carlo tree search (MCTS) has achieved state-of-the-art results in ...
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11/11/2020
Sim-To-Real Transfer for Miniature Autonomous Car Racing
Sim-to-real, a term that describes where a model is trained in a simulat...
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03/13/2020
Accelerating and Improving AlphaZero Using Population Based Training
AlphaZero has been very successful in many games. Unfortunately, it stil...
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05/31/2019
Multiple Policy Value Monte Carlo Tree Search
Many of the strongest game playing programs use a combination of Monte C...
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04/24/2019
Towards Combining On-Off-Policy Methods for Real-World Applications
In this paper, we point out a fundamental property of the objective in r...
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06/05/2018
Stochastic Gradient Descent with Hyperbolic-Tangent Decay
Learning rate scheduler has been a critical issue in the deep neural net...
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01/23/2018
Comparison Training for Computer Chinese Chess
This paper describes the application of comparison training (CT) for aut...
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05/30/2017
Multi-Labelled Value Networks for Computer Go
This paper proposes a new approach to a novel value network architecture...
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06/07/2016
