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  "access_rights": "",
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  "author": "Andr\u00b4e Sequeira",
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  "author": "Andr\u00b4e Sequeira",
            
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  "author_email": "",
            
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  "citation": [],
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2203.10591",
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  "defined_in": "https://doi.org/10.48550/arXiv.2203.10591",
            
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  "doi": "10.57702/ebuhalmc",
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  "doi": "10.57702/ebuhalmc",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-17",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Luis Paulo Santos",
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      "extra_author": "Luis Paulo Santos",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Luis Soares",
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      "extra_author": "Luis Soares",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Policy Gradients",
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      "display_name": "Policy Gradients",
            
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      "name": "policy-gradients",
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      "name": "policy-gradients",
            
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      "title": "Policy Gradients"
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      "title": "Policy Gradients"
            
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    },
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      "description": "",
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      "description": "",
            
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      "display_name": "Quantum Machine Learning",
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      "name": "quantum-machine-learning",
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      "name": "quantum-machine-learning",
            
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      "title": "Quantum Machine Learning"
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      "title": "Quantum Machine Learning"
            
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      "description": "",
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      "description": "",
            
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      "name": "reinforcement-learning",
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      "name": "reinforcement-learning",
            
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      "title": "Reinforcement Learning"
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      "title": "Reinforcement Learning"
            
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    }
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  "metadata_modified": "2024-12-17T12:13:58.937852",
            
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  "name": "policy-gradients-using-variational-quantum-circuits",
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  "name": "policy-gradients-using-variational-quantum-circuits",
            
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  "notes": "Variational Quantum Circuits are being used as versatile 
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  "notes": "Variational Quantum Circuits are being used as versatile 
            
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Quantum Machine Learning models. Some empirical results exhibit an 
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Quantum Machine Learning models. Some empirical results exhibit an 
            
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advantage in supervised and generative learning tasks. However, when 
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advantage in supervised and generative learning tasks. However, when 
            
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applied to Reinforcement Learning, less is known. In this work, we 
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applied to Reinforcement Learning, less is known. In this work, we 
            
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considered a Variational Quantum Circuit composed of a low-depth 
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considered a Variational Quantum Circuit composed of a low-depth 
            
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hardware-e\ufb03cient ansatz as the parameterized policy of a 
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hardware-e\ufb03cient ansatz as the parameterized policy of a 
            
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Reinforcement Learning agent.",
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Reinforcement Learning agent.",
            
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      "display_name": "Policy Gradients",
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      "display_name": "Policy Gradients",
            
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      "name": "Variational Quantum Circuits",
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  ],
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  "title": "Policy Gradients using Variational Quantum Circuits",
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  "title": "Policy Gradients using Variational Quantum Circuits",
            
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  "type": "dataset",
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  "version": ""
            
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}
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}