Answers.Body: <p>I think you are looking for <a href="https://arxiv.org/pdf/1611.09347.pdf" rel="nofollow noreferrer"><em>quantum machine learning</em> (QML)</a>, which is a relatively new field that sits at the intersection of quantum computing and machine learning.</p>
  <p>If you are not familiar with quantum computing (QC) and you are interested in QML, I suggest that you follow <a href="https://www.youtube.com/watch?v=VPsl_5RQe1A&amp;list=PLnhoxwUZN7-6hB2iWNhLrakuODLaxPTOG" rel="nofollow noreferrer">this course</a> by prof. Umesh Vazirani and read the book <a href="https://modphys.hosted.uark.edu/ETC/MISC/Quantum_Computing_for_Computer_Scientists_-_Yanofsky-cup-2008.pdf" rel="nofollow noreferrer">Quantum Computing for Computer Scientists</a> (2008) by Yanofsky and Mannucci. If you have a solid knowledge of linear algebra, you should not encounter big problems while learning QC. Be prepared to deal with the weirdness and beauty of qubits, quantum entanglement, and so on.</p>
  <p>If you want to directly dive into QML (although I am not familiar with the details of QML, I suggest that you first get familiar with the basics of QC, which I am familiar with) there are already several courses, <a href="https://arxiv.org/pdf/1611.09347.pdf" rel="nofollow noreferrer">papers</a>, <a href="https://www.tensorflow.org/quantum/concepts" rel="nofollow noreferrer">overviews</a>, and libraries (such as <a href="https://www.tensorflow.org/quantum" rel="nofollow noreferrer">TensorFlow Quantum</a>) on quantum machine learning.</p>
  <p>If you are interested in quantum reinforcement learning, maybe have a look at the paper <a href="https://arxiv.org/pdf/0810.3828.pdf" rel="nofollow noreferrer">Quantum Reinforcement Learning</a> (2008) by Daoyi Dong et al.</p>
  
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Answers.CreationDate: 2020-07-05T00:33:05.573Z
Answers.LastActivityDate: 2020-07-06T01:24:44.087Z
Answers.LastEditDate: 2020-07-06T01:24:44.087Z
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Body: <p>Assuming the definition of an agent to be:</p>
  <blockquote>
  <p>An entity that perceives its environment, processes the perceived information, and acts on the environment such that some goal is fulfilled.</p>
  </blockquote>
  <p>Are there any agents that are based on quantum processing/computing (i.e. implemented by a network of <a href="https://en.wikipedia.org/wiki/Quantum_logic_gate" rel="nofollow noreferrer">quantum gates</a>)?</p>
  <p>Is there any work done towards this end? If so, could someone provide references?</p>
  
Tags: <intelligent-agent><quantum-computing>
Title: Are there any agents that are based on quantum computing?
UserDisplayName: Varun Premkumar
ThreadText: # Are there any agents that are based on quantum computing?
  
  (Asked by: username_0 on 2020-07-03)
  
  Assuming the definition of an agent to be:
  
  > An entity that perceives its environment, processes the perceived information, and acts on the environment such that some goal is fulfilled.
  
  Are there any agents that are based on quantum processing/computing (i.e. implemented by a network of [quantum gates](https://en.wikipedia.org/wiki/Quantum_logic_gate))?
  
  Is there any work done towards this end? If so, could someone provide references?
  
  **Tags:** intelligent-agent, quantum-computing
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2020-07-05. Score: 3 | Accepted answer
  
  I think you are looking for [*quantum machine learning* (QML)](https://arxiv.org/pdf/1611.09347.pdf), which is a relatively new field that sits at the intersection of quantum computing and machine learning.
  
  If you are not familiar with quantum computing (QC) and you are interested in QML, I suggest that you follow [this course](https://www.youtube.com/watch?v=VPsl_5RQe1A&list=PLnhoxwUZN7-6hB2iWNhLrakuODLaxPTOG) by prof. Umesh Vazirani and read the book [Quantum Computing for Computer Scientists](https://modphys.hosted.uark.edu/ETC/MISC/Quantum_Computing_for_Computer_Scientists_-_Yanofsky-cup-2008.pdf) (2008) by Yanofsky and Mannucci. If you have a solid knowledge of linear algebra, you should not encounter big problems while learning QC. Be prepared to deal with the weirdness and beauty of qubits, quantum entanglement, and so on.
  
  If you want to directly dive into QML (although I am not familiar with the details of QML, I suggest that you first get familiar with the basics of QC, which I am familiar with) there are already several courses, [papers](https://arxiv.org/pdf/1611.09347.pdf), [overviews](https://www.tensorflow.org/quantum/concepts), and libraries (such as [TensorFlow Quantum](https://www.tensorflow.org/quantum)) on quantum machine learning.
  
  If you are interested in quantum reinforcement learning, maybe have a look at the paper [Quantum Reinforcement Learning](https://arxiv.org/pdf/0810.3828.pdf) (2008) by Daoyi Dong et al.
  
  
  ---
  
  