The Evolution of Reinforcement Learning in Quantitative Finance: A Survey
Fuente:
arXiv
Saved in:
| Main Authors: | Pippas, Nikolaos, Ludvig, Elliot A., Turkay, Cagatay |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction
by: Barry-Straume, Jostein, et al.
Published: (2026)
by: Barry-Straume, Jostein, et al.
Published: (2026)
Benchmarking Machine Learning Uncertainty Quantification Methodologies for Predicting Turbine Gas Temperature Degradation
by: Barry-Straume, Jostein, et al.
Published: (2026)
by: Barry-Straume, Jostein, et al.
Published: (2026)
A Novel Loss Function for Deep Learning Based Daily Stock Trading System
by: Guo, Ruoyu, et al.
Published: (2025)
by: Guo, Ruoyu, et al.
Published: (2025)
Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025)
by: Silue, Bram, et al.
Published: (2025)
Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning
by: Jiang, Zeyu, et al.
Published: (2025)
by: Jiang, Zeyu, et al.
Published: (2025)
Model Fusion via Retrofitting
by: Luenam, Phoomraphee, et al.
Published: (2025)
by: Luenam, Phoomraphee, et al.
Published: (2025)
A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction
by: Bogachov, Bogdan, et al.
Published: (2025)
by: Bogachov, Bogdan, et al.
Published: (2025)
Distributional Reinforcement Learning for Condition-Based Maintenance of Multi-Pump Equipment
by: Yasuno, Takato
Published: (2026)
by: Yasuno, Takato
Published: (2026)
Perfecting Aircraft Maneuvers with Reinforcement Learning
by: Cilan, Atahan, et al.
Published: (2026)
by: Cilan, Atahan, et al.
Published: (2026)
SQARL: A Size-Agnostic Reinforcement Learning approach for Circuit Allocation in Distributed Quantum Architectures
by: Carballo, Víctor, et al.
Published: (2026)
by: Carballo, Víctor, et al.
Published: (2026)
Data-Driven Assessment of Concrete Mixture Compositions on Chloride Transport via Standalone Machine Learning Algorithms
by: Aliasghar-Mamaghani, Mojtaba, et al.
Published: (2026)
by: Aliasghar-Mamaghani, Mojtaba, et al.
Published: (2026)
Improved Performances and Motivation in Intelligent Tutoring Systems: Combining Machine Learning and Learner Choice
by: Clément, Benjamin, et al.
Published: (2024)
by: Clément, Benjamin, et al.
Published: (2024)
When Hallucination Costs Millions: Benchmarking AI Agents in High-Stakes Adversarial Financial Markets
by: Dai, Zeshi, et al.
Published: (2025)
by: Dai, Zeshi, et al.
Published: (2025)
Centrally Coordinated Multi-Agent Reinforcement Learning for Power Grid Topology Control
by: de Mol, Barbera, et al.
Published: (2025)
by: de Mol, Barbera, et al.
Published: (2025)
Learning Controllable and Diverse Player Behaviors in Multi-Agent Environments
by: Cilan, Atahan, et al.
Published: (2025)
by: Cilan, Atahan, et al.
Published: (2025)
Dense Neural Network Based Arrhythmia Classification on Low-cost and Low-compute Micro-controller
by: Zishan, Md Abu Obaida, et al.
Published: (2025)
by: Zishan, Md Abu Obaida, et al.
Published: (2025)
Antibody Design and Optimization with Multi-scale Equivariant Graph Diffusion Models for Accurate Complex Antigen Binding
by: Chen, Jiameng, et al.
Published: (2025)
by: Chen, Jiameng, et al.
Published: (2025)
A Set-Sequence Model for Time Series
by: Epstein, Elliot L., et al.
Published: (2025)
by: Epstein, Elliot L., et al.
Published: (2025)
Forecasting Labor Markets with LSTNet: A Multi-Scale Deep Learning Approach
by: Nelson-Archer, Adam, et al.
Published: (2025)
by: Nelson-Archer, Adam, et al.
Published: (2025)
NormCode Canvas: Making LLM Agentic Workflows Development Sustainable via Case-Based Reasoning
by: Guan, Xin, et al.
Published: (2026)
by: Guan, Xin, et al.
Published: (2026)
Intelligent Design 4.0: Paradigm Evolution Toward the Agentic AI Era
by: Jiang, Shuo, et al.
Published: (2025)
by: Jiang, Shuo, et al.
Published: (2025)
Can Causal Discovery Algorithms Help in Generating Legal Arguments?
by: Wasmatkar, Soham, et al.
Published: (2026)
by: Wasmatkar, Soham, et al.
Published: (2026)
Developing the Reliable Shallow Supervised Learning for Thermal Comfort using ASHRAE RP-884 and ASHRAE Global Thermal Comfort Database II
by: Karyono, Kanisius, et al.
Published: (2023)
by: Karyono, Kanisius, et al.
Published: (2023)
Amortized Molecular Optimization via Group Relative Policy Optimization
by: Javaid, Muhammad bin, et al.
Published: (2026)
by: Javaid, Muhammad bin, et al.
Published: (2026)
Kolmogorov Arnold Networks and Multi-Layer Perceptrons: A Paradigm Shift in Neural Modelling
by: Gaonkar, Aradhya, et al.
Published: (2026)
by: Gaonkar, Aradhya, et al.
Published: (2026)
ASD-Bench: A Four-Axis Comprehensive Benchmark of AI Models for Autism Spectrum Disorder
by: Singh, Shubhankit, et al.
Published: (2026)
by: Singh, Shubhankit, et al.
Published: (2026)
EvoIdeator: Evolving Scientific Ideas through Checklist-Grounded Reinforcement Learning
by: Sauter, Andreas, et al.
Published: (2026)
by: Sauter, Andreas, et al.
Published: (2026)
TML-Bench: Benchmark for Data Science Agents on Tabular ML Tasks
by: Pinchuk, Mykola
Published: (2026)
by: Pinchuk, Mykola
Published: (2026)
TextCAVs: Debugging vision models using text
by: Nicolson, Angus, et al.
Published: (2024)
by: Nicolson, Angus, et al.
Published: (2024)
Multi-Agent Pathfinding with Non-Unit Integer Edge Costs via Enhanced Conflict-Based Search and Graph Discretization
by: Fan, Hongkai, et al.
Published: (2026)
by: Fan, Hongkai, et al.
Published: (2026)
Augmenting deep neural networks with symbolic knowledge: Towards trustworthy and interpretable AI for education
by: Hooshyar, Danial, et al.
Published: (2023)
by: Hooshyar, Danial, et al.
Published: (2023)
One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents
by: Hong, Yoosung
Published: (2026)
by: Hong, Yoosung
Published: (2026)
When Fairness Metrics Disagree: Evaluating the Reliability of Demographic Fairness Assessment in Machine Learning
by: Alsayed, Khalid Adnan
Published: (2026)
by: Alsayed, Khalid Adnan
Published: (2026)
SUN Team's Contribution to ABAW 2024 Competition: Audio-visual Valence-Arousal Estimation and Expression Recognition
by: Dresvyanskiy, Denis, et al.
Published: (2024)
by: Dresvyanskiy, Denis, et al.
Published: (2024)
SCAFDS: Edge-Feature Graph Attention for Interbank Fraud Detection with Attribution-Grounded SAR Generation
by: Uddin, Mohammad Nasir
Published: (2026)
by: Uddin, Mohammad Nasir
Published: (2026)
Learning Approximate Nash Equilibria in Cooperative Multi-Agent Reinforcement Learning via Mean-Field Subsampling
by: Anand, Emile, et al.
Published: (2026)
by: Anand, Emile, et al.
Published: (2026)
TelePlanNet: An AI-Driven Framework for Efficient Telecom Network Planning
by: Deng, Zongyuan, et al.
Published: (2025)
by: Deng, Zongyuan, et al.
Published: (2025)
GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
by: Agrawal, Lakshya A, et al.
Published: (2025)
by: Agrawal, Lakshya A, et al.
Published: (2025)
VGC-Bench: Towards Mastering Diverse Team Strategies in Competitive Pokémon
by: Angliss, Cameron, et al.
Published: (2025)
by: Angliss, Cameron, et al.
Published: (2025)
Feature space reduction method for ultrahigh-dimensional, multiclass data: Random forest-based multiround screening (RFMS)
by: Hanczár, Gergely, et al.
Published: (2023)
by: Hanczár, Gergely, et al.
Published: (2023)
Similar Items
-
Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction
by: Barry-Straume, Jostein, et al.
Published: (2026) -
Benchmarking Machine Learning Uncertainty Quantification Methodologies for Predicting Turbine Gas Temperature Degradation
by: Barry-Straume, Jostein, et al.
Published: (2026) -
A Novel Loss Function for Deep Learning Based Daily Stock Trading System
by: Guo, Ruoyu, et al.
Published: (2025) -
Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025) -
Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning
by: Jiang, Zeyu, et al.
Published: (2025)