video:“A Distributional Perspective on Reinforcement Learning” https://buff.ly/2x9Nm6h Article: A Brief Survey of Deep Reinforcement Learning, http://goo.gl/eTTWM9 #google #deepLearning
#Google releases #MachineLearning Crash Course with #Python and #TensorFlow APIs! http://goo.gl/kIEHFH @ArtificialIntelligenceArticles
A wonderful comprehensive read from #Google_Brain and #DeepmindAI on the challenges which we can come across while implementing RL on real-world systems.
Paper-Title: Challenges of Real-World Reinforcement learning
Link to the paper: https://arxiv.org/abs/1904.12901
They highlighted 9 most important challenges as follows:
1. Training off-line from the fixed logs of an external behavior policy.
2. Learning on the real system from limited samples.
3. High-dimensional continuous state and action spaces.
4. Safety constraints that should never or at least rarely be violated.
5. Tasks that may be partially observable, alternatively viewed as non-stationary or stochastic.
6. Reward functions that are unspecified, multi-objective,or risk-sensitive.
7. System operators who desire explainable policies and actions.
8. Inference that must happen in real-time at the controlfrequency of the system.
9. Large and/or unknown delays in the system actuators,sensors, or rewards.
Paper-Title: Challenges of Real-World Reinforcement learning
Link to the paper: https://arxiv.org/abs/1904.12901
They highlighted 9 most important challenges as follows:
1. Training off-line from the fixed logs of an external behavior policy.
2. Learning on the real system from limited samples.
3. High-dimensional continuous state and action spaces.
4. Safety constraints that should never or at least rarely be violated.
5. Tasks that may be partially observable, alternatively viewed as non-stationary or stochastic.
6. Reward functions that are unspecified, multi-objective,or risk-sensitive.
7. System operators who desire explainable policies and actions.
8. Inference that must happen in real-time at the controlfrequency of the system.
9. Large and/or unknown delays in the system actuators,sensors, or rewards.
arXiv.org
Challenges of Real-World Reinforcement Learning
Reinforcement learning (RL) has proven its worth in a series of artificial domains, and is beginning to show some successes in real-world scenarios. However, much of the research advances in RL...
What kind of medical innovations can we see in 2019? Also, is Google and Microsoft taking the lead?
https://t.ly/Zj3m9
Blog Post Version: https://bit.ly/31tFbRD
#Medical #ArtificialIntelligence #healthcare #HealthTech #opioids #opioidcrisis #Google #Microsoft #AI #money
https://t.ly/Zj3m9
Blog Post Version: https://bit.ly/31tFbRD
#Medical #ArtificialIntelligence #healthcare #HealthTech #opioids #opioidcrisis #Google #Microsoft #AI #money
YouTube
10 Medical Innovation in the current Year….is Google and Microsoft taking the lead?
What kind of Medical innovation can we expect to see in the near future? And are the tech giants take the lead? Uploaded another version with louder Audio: h...