ECF: A C++ framework for evolutionary computation
Deep Reinforcement Learning for Goal-Based Investing Under Regime-Switching
Leveraging More of Biology in Evolutionary Reinforcement Learning
Deep Reinforcement Learning for Robust Goal-Based Wealth Management
On Evolvability and Behavior Landscapes in Neuroevolutionary Divergent Search
A New Angle: On Evolving Rotation Symmetric Boolean Functions
A Search for Nonlinear Balanced Boolean Functions by Leveraging Phenotypic Properties
Finding Near-Optimal Portfolios with Quality-Diversity
Deep Reinforcement Learning for Robust Goal-Based Wealth Management
Deep reinforcement learning for market making with time- varying order arrival intensities
Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model
Reinforcement Learning Approaches to Optimal Market Making
Market Making With Signals Through Deep Reinforcement Learning
Adaptive rolling window selection for minimum variance portfolio estimation based on reinforcement learning
Latest updates (!):
12 June 2023 - became a guest co-editor for the special issue "Algorithms in Evolutionary Reinforcement Learning", Algorithms journal
| Gašperov, Bruno, and Zvonko Kostanjčar. "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model." IEEE Control Systems Letters (2022).
| Gašperov, Bruno, and Zvonko Kostanjčar. "Market Making With Signals Through Deep Reinforcement Learning." IEEE Access 9 (2021): 61611-61622.
| Gašperov, Bruno, et al. "Reinforcement Learning Approaches to Optimal Market Making." Mathematics 9.21 (2021): 2689.
| Gašperov, Bruno, et al. "Adaptive rolling window selection for minimum variance portfolio estimation based on reinforcement learning." 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO). IEEE, 2020
Teaching
University graduate
- Mathematics of Finance (Seminar)
Competences
-
Computational and artificial intelligence
Machine learning Statistical learning Prediction methods Neural networks -
Mathematics
Optimization Probability Bayes methods Sampling methods Stochastic processes -
Computational and artificial intelligence
Machine learning Statistical learning Prediction methods Neural networks