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Deep imitation learning for 3D navigation tasks
Ahmed Hussein
, Eyad Elyan
, Mohamed Medhat Gaber
,
Chrisina Jayne
SCEDT School Executive Team
Research output
:
Contribution to journal
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Article
›
peer-review
188
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Keyphrases
Navigation Task
100%
Deep Imitation Learning
100%
3D Navigation
100%
Learning from Experience
60%
3D Environment
40%
Intelligent Agents
40%
Active Learning
40%
Imitation Learning
40%
Visual Input
40%
Deep Reinforcement Learning (deep RL)
40%
Reinforcement Learning Algorithm
40%
Popular
20%
Learning Methods
20%
Unseen
20%
Typical Problems
20%
Deep Learning
20%
Deep Learning Methods
20%
Generalization Ability
20%
Learning from Demonstration
20%
High-dimensional Data
20%
Effective Policy
20%
Deep Convolutional Neural Network (deep CNN)
20%
Delayed Reward
20%
Learning by Imitation
20%
Deep Q-network
20%
Actor-critic
20%
Long Trajectory
20%
Learning Efficiency
20%
Real Application
20%
Computer Science
Navigation Task
100%
Intelligent Agent
40%
Active Learning
40%
Deep Reinforcement Learning
40%
Learning Technique
20%
Reinforcement Learning
20%
Generalization Ability
20%
Deep Learning Technique
20%
High Dimensional Data
20%
Simulated Environment
20%
Deep Q-Network
20%
Deep Convolutional Neural Networks
20%
Real Application
20%
Deep Learning Method
20%
Psychology
Neural Network
100%