Giuseppe Cuccu

Research Statement

Machine learning methods are often designed to work on data which is clean, precise and readily available; meanwhile real-world applications typically provide data which is incomplete, sparse and often misleading. Real-time performance is often a requirement, along with generalization to unseen conditions and limited reliance on prior knowledge or bootstrapping. My research aims at addressing control problems through reinforcement learning neuroevolution, by taking on each problem in isolation while keeping into perspective dynamic applications, and ultimately assembling systems capable of wide adaptation.

Keywords

Machine Learning, Neuroevolution, Recurrent Neural Networks, Evolutionary Algorithms, Unsupervised Learning, Parallel Computing, Artificial Intelligence.

Publications

1. Giuseppe Cuccu, Julian Togelius, and Philippe Cudré-Mauroux. “Playing Atari with Six Neurons.” ArXiv e-Prints, 2018. Bibtex PDF

   Playing Atari with Six Neurons

   Giuseppe Cuccu, Julian Togelius, and Philippe Cudré-Mauroux. “Playing Atari with Six Neurons.” ArXiv e-Prints, 2018.

   @article{cuccu2018arxiv,
     title = {Playing Atari with Six Neurons},
     author = {Cuccu, Giuseppe and Togelius, Julian and Cudr{\'e}-Mauroux, Philippe},
     journal = {ArXiv e-prints},
     archiveprefix = {arXiv},
     eprint = {1806.01363},
     primaryclass = {cs.LG},
     url = {https://exascale.info/assets/pdf/cuccu2018arxiv.pdf},
     year = {2018}
   }
   

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2. Giuseppe Cuccu, Somayeh Danafar, Philippe Cudré-Mauroux, Martin Gassner, Stefano Bernero, and Krzysztof Kryszczuk. “A Data-Driven Approach to Predict NOx-Emissions of Gas Turbines.” In 2017 IEEE International Conference on Big Data, BigData 2017, Boston, MA, USA, December 11-14, 2017, 1283–88, 2017. Bibtex PDF

   A data-driven approach to predict NOx-emissions of gas turbines

   Giuseppe Cuccu, Somayeh Danafar, Philippe Cudré-Mauroux, Martin Gassner, Stefano Bernero, and Krzysztof Kryszczuk. “A Data-Driven Approach to Predict NOx-Emissions of Gas Turbines.” In 2017 IEEE International Conference on Big Data, BigData 2017, Boston, MA, USA, December 11-14, 2017, 1283–88, 2017.

   @inproceedings{cuccu2017bigdata,
     author = {Cuccu, Giuseppe and Danafar, Somayeh and Cudr{\'e}-Mauroux, Philippe and Gassner, Martin and Bernero, Stefano and Kryszczuk, Krzysztof},
     title = {A data-driven approach to predict NOx-emissions of gas turbines},
     booktitle = {2017 {IEEE} International Conference on Big Data, BigData 2017, Boston,
                    MA, USA, December 11-14, 2017},
     pages = {1283--1288},
     year = {2017},
     doi = {10.1109/BigData.2017.8258056},
     url = {https://exascale.info/assets/pdf/cuccu2017bigdata.pdf}
   }
   

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3. Jan Koutník, Giuseppe Cuccu, Jürgen Schmidhuber, and Faustino Gomez. “Evolving Large-Scale Neural Networks for Vision-Based Reinforcement Learning.” In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, 1061–68. GECCO ’13. ACM, 2013. Bibtex PDF

   Evolving Large-scale Neural Networks for Vision-based Reinforcement Learning

   Jan Koutník, Giuseppe Cuccu, Jürgen Schmidhuber, and Faustino Gomez. “Evolving Large-Scale Neural Networks for Vision-Based Reinforcement Learning.” In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, 1061–68. GECCO ’13. ACM, 2013.

   @inproceedings{koutnik_evolving_rl_2013,
     location = {New York, {NY}, {USA}},
     title = {Evolving Large-scale Neural Networks for Vision-based Reinforcement Learning},
     isbn = {978-1-4503-1963-8},
     url = {https://pdfs.semanticscholar.org/fe4d/de1ea2fb09e65b990ce0c661ef151301dae4.pdf},
     doi = {10.1145/2463372.2463509},
     series = {{GECCO} '13},
     pages = {1061--1068},
     booktitle = {Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation},
     publisher = {{ACM}},
     author = {Koutník, Jan and Cuccu, Giuseppe and Schmidhuber, Jürgen and Gomez, Faustino},
     year = {2013},
     keywords = {Computer vision, neuroevolution, recurrent neural networks, reinforcement learning}
   }
   

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4. Jan Koutník, Giuseppe Cuccu, Jürgen Schmidhuber, and Faustino Gomez. “Evolving Large-Scale Neural Networks for Vision-Based TORCS.” In Foundations of Digital Games (FDG), 206–12, 2013. Bibtex PDF

   Evolving Large-Scale Neural Networks for Vision-Based TORCS

   Jan Koutník, Giuseppe Cuccu, Jürgen Schmidhuber, and Faustino Gomez. “Evolving Large-Scale Neural Networks for Vision-Based TORCS.” In Foundations of Digital Games (FDG), 206–12, 2013.

   @inproceedings{koutnik_evolving_torcs_2013,
     location = {Chania, Crete, {GR}},
     title = {Evolving Large-Scale Neural Networks for Vision-Based {TORCS}},
     isbn = {{ISBN} 978-0-9913982-0-1},
     url = {https://pdfs.semanticscholar.org/0def/2a43a183a9579f67c7170867ee10917e6115.pdf},
     pages = {206--212},
     booktitle = {Foundations of Digital Games (FDG)},
     author = {Koutník, Jan and Cuccu, Giuseppe and Schmidhuber, Jürgen and Gomez, Faustino},
     year = {2013}
   }
   

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5. Giuseppe Cuccu, and Faustino Gomez. “Block Diagonal Natural Evolution Strategies.” In Parallel Problem Solving from Nature - PPSN XII, 488–97. Springer, Berlin, Heidelberg, 2012. Bibtex PDF

   Block Diagonal Natural Evolution Strategies

   Giuseppe Cuccu, and Faustino Gomez. “Block Diagonal Natural Evolution Strategies.” In Parallel Problem Solving from Nature - PPSN XII, 488–97. Springer, Berlin, Heidelberg, 2012.

   @inproceedings{cuccu_block_2012,
     title = {Block Diagonal Natural Evolution Strategies},
     url = {https://pdfs.semanticscholar.org/7188/787665b3f79216716061510cb8185d711524.pdf},
     doi = {10.1007/978-3-642-32964-7_49},
     eventtitle = {International Conference on Parallel Problem Solving from Nature},
     pages = {488--497},
     booktitle = {Parallel Problem Solving from Nature - {PPSN} {XII}},
     publisher = {Springer, Berlin, Heidelberg},
     author = {Cuccu, Giuseppe and Gomez, Faustino},
     year = {2012},
     langid = {english}
   }
   

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6. Leonardo Vanneschi, and Giuseppe Cuccu. “Reconstructing Dynamic Target Functions by Means of Genetic Programming Using Variable Population Size.” In Computational Intelligence, 343:121–34. Springer, Berlin, Heidelberg, 2011. Bibtex PDF

   Reconstructing Dynamic Target Functions by Means of Genetic Programming Using Variable Population Size

   Leonardo Vanneschi, and Giuseppe Cuccu. “Reconstructing Dynamic Target Functions by Means of Genetic Programming Using Variable Population Size.” In Computational Intelligence, 343:121–34. Springer, Berlin, Heidelberg, 2011.

   @incollection{vanneschi_reconstructing_2011,
     title = {Reconstructing Dynamic Target Functions by Means of Genetic Programming Using Variable Population Size},
     volume = {343},
     url = {https://link.springer.com/chapter/10.1007/978-3-642-20206-3_8},
     pages = {121--134},
     booktitle = {Computational Intelligence},
     publisher = {Springer, Berlin, Heidelberg},
     author = {Vanneschi, Leonardo and Cuccu, Giuseppe},
     year = {2011},
     langid = {english},
     doi = {10.1007/978-3-642-20206-3_8}
   }
   

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7. Vincent Graziano, Tobias Glasmachers, Tom Schaul, Leo Pape, Giuseppe Cuccu, Jürgen Leitner, and Jürgen Schmidhuber. “Artificial Curiosity for Autonomous Space Exploration.” Acta Futura 4 (2011): 41–51. Bibtex PDF

   Artificial Curiosity for Autonomous Space Exploration

   Vincent Graziano, Tobias Glasmachers, Tom Schaul, Leo Pape, Giuseppe Cuccu, Jürgen Leitner, and Jürgen Schmidhuber. “Artificial Curiosity for Autonomous Space Exploration.” Acta Futura 4 (2011): 41–51.

   @article{graziano_artificial_2011,
     title = {Artificial Curiosity for Autonomous Space Exploration},
     volume = {4},
     url = {https://pdfs.semanticscholar.org/2809/ea3e24f3b07b3b613929d8517a381956e7de.pdf},
     pages = {41--51},
     journaltitle = {Acta Futura},
     author = {Graziano, Vincent and Glasmachers, Tobias and Schaul, Tom and Pape, Leo and Cuccu, Giuseppe and Leitner, Jürgen and Schmidhuber, Jürgen},
     year = {2011}
   }
   

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8. Giuseppe Cuccu, Matthew Luciw, Jürgen Schmidhuber, and Faustino Gomez. “Intrinsically Motivated Neuroevolution for Vision-Based Reinforcement Learning.” In Development and Learning (ICDL), 2011 IEEE International Conference On, 2:1–7. IEEE, 2011. Bibtex PDF

   Intrinsically Motivated Neuroevolution for Vision-based Reinforcement Learning

   Giuseppe Cuccu, Matthew Luciw, Jürgen Schmidhuber, and Faustino Gomez. “Intrinsically Motivated Neuroevolution for Vision-Based Reinforcement Learning.” In Development and Learning (ICDL), 2011 IEEE International Conference On, 2:1–7. IEEE, 2011.

   @inproceedings{cuccu_intrinsically_2011,
     title = {Intrinsically Motivated Neuroevolution for Vision-based Reinforcement Learning},
     volume = {2},
     url = {https://pdfs.semanticscholar.org/92ab/fe027e903c94683c1c751a6e854744303b84.pdf},
     pages = {1--7},
     booktitle = {Development and Learning ({ICDL}), 2011 {IEEE} International Conference on},
     publisher = {{IEEE}},
     author = {Cuccu, Giuseppe and Luciw, Matthew and Schmidhuber, Jürgen and Gomez, Faustino},
     year = {2011},
     keywords = {artificial evolution, Computer vision, continuous reinforcement learning, embedded agents, high-dimensional visual images, intrinsically motivated neuroevolution, learning (artificial intelligence), neural networks, recurrent neural nets, recurrent neural network controllers, Tin, unsupervised sensory preprocessor, vision-based reinforcement learning, Yttrium}
   }
   

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9. Giuseppe Cuccu, Faustino Gomez, and Tobias Glasmachers. “Novelty-Based Restarts for Evolution Strategies.” In Evolutionary Computation (CEC), 2011 IEEE Congress On, 158–63. IEEE, 2011. Bibtex PDF

   Novelty-based Restarts for Evolution Strategies

   Giuseppe Cuccu, Faustino Gomez, and Tobias Glasmachers. “Novelty-Based Restarts for Evolution Strategies.” In Evolutionary Computation (CEC), 2011 IEEE Congress On, 158–63. IEEE, 2011.

   @inproceedings{cuccu_novelty-based_2011,
     title = {Novelty-based Restarts for Evolution Strategies},
     url = {https://pdfs.semanticscholar.org/94a7/20b35e96eaa41e0b38656f5db94f583ba8e5.pdf},
     pages = {158--163},
     booktitle = {Evolutionary Computation ({CEC}), 2011 {IEEE} Congress on},
     publisher = {{IEEE}},
     author = {Cuccu, Giuseppe and Gomez, Faustino and Glasmachers, Tobias},
     year = {2011},
     keywords = {black box optimization, black-box optimization, black box search algorithm, Convergence, Covariance matrix, Equations, evolutionary computation, evolution strategies, Monte Carlo methods, novelty-based restarts, novelty search, optimisation, Optimization, restart strategies, search problems, search space, Switches}
   }
   

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10. Giuseppe Cuccu, and Faustino Gomez. “When Novelty Is Not Enough.” In Applications of Evolutionary Computation, 234–43. Springer, Berlin, Heidelberg, 2011. Bibtex PDF

    When Novelty Is Not Enough

    Giuseppe Cuccu, and Faustino Gomez. “When Novelty Is Not Enough.” In Applications of Evolutionary Computation, 234–43. Springer, Berlin, Heidelberg, 2011.

    @inproceedings{cuccu_when_2011,
      title = {When Novelty Is Not Enough},
      url = {https://pdfs.semanticscholar.org/5030/2f1693273fa64aab40fd9732381767b3337e.pdf},
      doi = {10.1007/978-3-642-20525-5_24},
      eventtitle = {European Conference on the Applications of Evolutionary Computation},
      pages = {234--243},
      booktitle = {Applications of Evolutionary Computation},
      publisher = {Springer, Berlin, Heidelberg},
      author = {Cuccu, Giuseppe and Gomez, Faustino},
      year = {2011},
      langid = {english}
    }
    

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11. Leonardo Vanneschi, and Giuseppe Cuccu. “Variable Size Population for Dynamic Optimization with Genetic Programming.” In Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, 1895–96. GECCO ’09. ACM, 2009. Bibtex PDF

    Variable Size Population for Dynamic Optimization with Genetic Programming

    Leonardo Vanneschi, and Giuseppe Cuccu. “Variable Size Population for Dynamic Optimization with Genetic Programming.” In Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, 1895–96. GECCO ’09. ACM, 2009.

    @inproceedings{vanneschi_variable_2009,
      author = {Vanneschi, Leonardo and Cuccu, Giuseppe},
      location = {New York, {NY}, {USA}},
      title = {Variable Size Population for Dynamic Optimization with Genetic Programming},
      isbn = {978-1-60558-325-9},
      url = {https://pdfs.semanticscholar.org/ed3a/0e0ddad1bb698f2e8a04fa74d10177662703.pdf},
      doi = {10.1145/1569901.1570222},
      series = {{GECCO} '09},
      pages = {1895--1896},
      booktitle = {Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation},
      publisher = {{ACM}},
      year = {2009},
      keywords = {dynamic optimization, genetic algorithms, genetic programming, genetic programming, Poster, variable size populations}
    }
    

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12. Leonardo Vanneschi, and Giuseppe Cuccu. “A Study of Genetic Programming Variable Population Size for Dynamic Optimization Problems.” In International Conference on Evolutionary Computation (ICEC), 119–26, 2009. Bibtex PDF

    A Study of Genetic Programming Variable Population Size for Dynamic Optimization Problems

    Leonardo Vanneschi, and Giuseppe Cuccu. “A Study of Genetic Programming Variable Population Size for Dynamic Optimization Problems.” In International Conference on Evolutionary Computation (ICEC), 119–26, 2009.

    @inproceedings{vanneschi_study_2009,
      author = {Vanneschi, Leonardo and Cuccu, Giuseppe},
      location = {Madeira, Portugal},
      title = {A Study of Genetic Programming Variable Population Size for Dynamic Optimization Problems},
      url = {https://pdfs.semanticscholar.org/f0e0/aff77a512fbddaf66caa6916785aa79adc07.pdf},
      pages = {119--126},
      booktitle = {International Conference on Evolutionary Computation (ICEC)},
      year = {2009},
      keywords = {genetic algorithms, genetic programming}
    }
    

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