Edoardo Conti
Impact in
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- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Artificial Intelligence in Games
- Neural Networks and Reservoir Computing
- Domain Adaptation and Few-Shot Learning
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- Adaptive Dynamic Programming Control
- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Inflammatory mediators and NSAID effects 1
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- Neural Networks and Reservoir Computing 1
- Reinforcement Learning in Robotics 1
- Metaheuristic Optimization Algorithms Research 1
- Co-authors
- Kenneth O. Stanley (1 shared paper)Joel Lehman (1 shared paper)Vashisht Madhavan (1 shared paper)Jeff Clune (1 shared paper)Felipe Petroski Such (1 shared paper)David Guijo-Rubio (1 shared paper)Riccardo Rosati (1 shared paper)Primo Zingaretti (1 shared paper)
- Journals
- Lecture notes in computer science (1 paper)Università Politecnica delle Marche (Università Politecnica delle Marche) (1 paper)Neural Information Processing Systems (1 paper)
- Partner nations
- ItalyDenmarkUnited States
In The Last Decade
Edoardo Conti
2 papers receiving 54 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 48
- Computational Theory and Mathematics 17
- Health Informatics 1
- Management Science and Operations Research 4
- Cognitive Neuroscience 5
Countries citing papers authored by Edoardo Conti
This map shows the geographic impact of Edoardo Conti's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Edoardo Conti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edoardo Conti more than expected).
Fields of papers citing papers by Edoardo Conti
This network shows the impact of papers produced by Edoardo Conti. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Edoardo Conti. The network helps show where Edoardo Conti may publish in the future.
Co-authors
The 13 scholars most cited alongside Edoardo Conti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents | 2018 | 58 |
| 2 | 2024 | 1 | |
| 3 | 2025 | 0 |
About Edoardo Conti
Edoardo Conti is a scholar working on Pharmacology, Artificial Intelligence, Rheumatology, Radiology, Nuclear Medicine and Imaging and Complementary and alternative medicine, having authored 3 papers that have together received 59 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (1 paper), Osteoarthritis Treatment and Mechanisms (1 paper), Neural Networks and Reservoir Computing (1 paper), Inflammatory mediators and NSAID effects (1 paper), Traditional Chinese Medicine Studies (1 paper), Reinforcement Learning in Robotics (1 paper), COVID-19 diagnosis using AI (1 paper) and Metaheuristic Optimization Algorithms Research (1 paper). The work is most often cited by research in Artificial Intelligence (48 citations), Computational Theory and Mathematics (17 citations), Health Informatics (1 citation), Management Science and Operations Research (4 citations) and Cognitive Neuroscience (5 citations). Edoardo Conti has collaborated with scholars based in Italy, Denmark and United States. Frequent co-authors include Kenneth O. Stanley, Joel Lehman, Vashisht Madhavan, Jeff Clune, Felipe Petroski Such, David Guijo-Rubio, Riccardo Rosati, Primo Zingaretti, Pedro Antonio Gutiérrez and Luca Romeo. Their work appears in journals such as Lecture notes in computer science, Università Politecnica delle Marche (Università Politecnica delle Marche) and Neural Information Processing Systems.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.