47 citations · 155 across the 17 of their papers we have counts for
8 papers · 1 filter
Deep Crowd Anomaly Detection: State-of-the-Art, Challenges, and Future Research Directions
Md. Haidar Sharif, Lei Jiao, Christian W. Omlin
Crowd anomaly detection is one of the most popular topics in computer vision in the context of smart cities. A plethora of deep learning methods have been proposed that generally o…
Symbolic Explanation of Affinity-Based Reinforcement Learning Agents with Markov Models
Charl Maree, Christian W. Omlin
The proliferation of artificial intelligence is increasingly dependent on model understanding. Understanding demands both an interpretation - a human reasoning about a model's beha…
Towards Artificial Virtuous Agents: Games, Dilemmas and Machine Learning
Ajay Vishwanath, Einar Duenger Bøhn, Ole-Christoffer Granmo +2
Machine ethics has received increasing attention over the past few years because of the need to ensure safe and reliable artificial intelligence (AI). The two dominantly used theor…
Balancing Profit, Risk, and Sustainability for Portfolio Management
Charl Maree, Christian W. Omlin
Stock portfolio optimization is the process of continuous reallocation of funds to a selection of stocks. This is a particularly well-suited problem for reinforcement learning, as…
Towards Responsible AI for Financial Transactions
Charl Maree, Jan Erik Modal, Christian W. Omlin
The application of AI in finance is increasingly dependent on the principles of responsible AI. These principles - explainability, fairness, privacy, accountability, transparency a…
Reinforcement Learning with Intrinsic Affinity for Personalized Prosperity Management
Charl Maree, Christian W. Omlin
The common purpose of applying reinforcement learning (RL) to asset management is the maximization of profit. The extrinsic reward function used to learn an optimal strategy typica…
Can Interpretable Reinforcement Learning Manage Prosperity Your Way?
Charl Maree, Christian Omlin
Personalisation of products and services is fast becoming the driver of success in banking and commerce. Machine learning holds the promise of gaining a deeper understanding of and…
Reinforcement Learning Your Way: Agent Characterization through Policy Regularization
Charl Maree, Christian Omlin
The increased complexity of state-of-the-art reinforcement learning (RL) algorithms have resulted in an opacity that inhibits explainability and understanding. This has led to the…