4 Matching Annotations
- Nov 2023
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serpdotai.gitbook.io serpdotai.gitbook.io
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Actor-critic is a temporal difference algorithm used in reinforcement learning. It consists of two networks: the actor, which decides which action to take, and the critic, which evaluates the action produced by the actor by computing the value function and informs the actor how good the action was and how it should adjust. In simple terms, the actor-critic is a temporal difference version of policy gradient. The learning of the actor is based on a policy gradient approach.
Actor-critic
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- Mar 2021
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academic.oup.com academic.oup.com
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Blakely, Tony, John Lynch, Koen Simons, Rebecca Bentley, and Sherri Rose. ‘Reflection on Modern Methods: When Worlds Collide—Prediction, Machine Learning and Causal Inference’. International Journal of Epidemiology 49, no. 6 (1 December 2020): 2058–64. https://doi.org/10.1093/ije/dyz132.
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- Sep 2020
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psyarxiv.com psyarxiv.com
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Yang, Scott Cheng-Hsin, Chirag Rank, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto. ‘Unifying Recommendation and Active Learning for Information Filtering and Recommender Systems’. Preprint. PsyArXiv, 25 August 2020. https://doi.org/10.31234/osf.io/jqa83.
Tags
- predictive accuracy
- exploration-exploitation tradeoff
- algorithms
- Internet
- machine learning
- cognitive science
- is:preprint
- recommendation accuracy
- artificial intelligence
- parameterized model
- active learning
- AI
- computer science
- recommender system
- information filtering
- lang:en
- experimental approach
Annotators
URL
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- Jul 2019
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www.oreilly.com www.oreilly.com
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Machine learning models are basically mathematical functions that represent the relationship between different aspects of data.
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