Matteo Pirotta
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 5%
- Control and Systems Engineering
- Management Science and Operations Research top 10%
- Electrical and Electronic Engineering
- Co-authors
- Marcello RestelliSimone ParisiLuca BascettaJan PetersAlessandra PedrocchiEric RojasEmilia AmbrosiniSimona Ferrante
- Topics
- Reinforcement Learning in Robotics (19 papers)Advanced Multi-Objective Optimization Algorithms (7 papers)Advanced Bandit Algorithms Research (7 papers)
In The Last Decade
Matteo Pirotta
26 papers receiving 251 citations
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 174
- Computational Theory and Mathematics 99
- Control and Systems Engineering 48
- Management Science and Operations Research 46
- Electrical and Electronic Engineering 33
Countries citing papers authored by Matteo Pirotta
This map shows the geographic impact of Matteo Pirotta'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 Matteo Pirotta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Pirotta more than expected).
Fields of papers citing papers by Matteo Pirotta
This network shows the impact of papers produced by Matteo Pirotta. 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 Matteo Pirotta. The network helps show where Matteo Pirotta may publish in the future.
Co-authorship network of co-authors of Matteo Pirotta
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Pirotta. A scholar is included among the top collaborators of Matteo Pirotta based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matteo Pirotta. Matteo Pirotta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Gaussian Approximation for Bias Reduction in Q-Learning | 4 |
| 2 | Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach | 4 |
| 3 | Active Model Estimation in Markov Decision Processes. | 0 |
| 4 | No-regret exploration in goal-oriented reinforcement learning | 0 |
| 5 | 4 | |
| 6 | Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs | 3 |
| 7 | Importance Weighted Transfer of Samples in Reinforcement Learning | 2 |
| 8 | 31 | |
| 9 | 5 | |
| 10 | 26 | |
| 11 | Reinforcement learning: from theory to algorithms | 2 |
| 12 | 2 | |
| 13 | 2 | |
| 14 | 10 | |
| 15 | 27 | |
| 16 | 31 | |
| 17 | Adaptive Step-Size for Policy Gradient Methods | 22 |
| 18 | Safe Policy Iteration | 12 |
| 19 | 2 | |
| 20 | Fitted Policy Search: Direct Policy Search using a Batch Reinforcement Learning Approach | 1 |
About Matteo Pirotta
Matteo Pirotta is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research, having authored 28 papers that have together received 265 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (19 papers), Advanced Multi-Objective Optimization Algorithms (7 papers) and Advanced Bandit Algorithms Research (7 papers). The work is most often cited by research in Computational Theory and Mathematics (99 citations), Artificial Intelligence (174 citations) and Management Science and Operations Research (46 citations). Matteo Pirotta has collaborated with scholars based in Italy, Israel and Germany. Frequent co-authors include Marcello Restelli, Simone Parisi, Luca Bascetta, Jan Peters, Alessandra Pedrocchi, Eric Rojas, Emilia Ambrosini, Simona Ferrante, Luigi Piroddi and Alessandro Lazaric. Their work appears in journals such as IEEE Transactions on Cybernetics, Neurocomputing and Machine Learning.
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.