Emergence of Scenario-Appropriate Collaborative Behaviors for Teams of Robotic Bodyguards. - Hassam Ullah Sheikh; Ladislau Bölöni (AAMAS, 2019)

Learning Distributed Cooperative Policies for Security Games via Deep Reinforcement Learning. - Hassam Ullah Sheikh; Mina Razghandi; Ladislau Bölöni (COMPSAC (1), 2019)

The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning. - Hassam Ullah Sheikh; Ladislau Bölöni (CoRR, 2019)

Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning. - Hassam Ullah Sheikh; Ladislau Bölöni (CoRR, 2019)

Universal Policies to Learn Them All. - Hassam Ullah Sheikh; Ladislau Bölöni (CoRR, 2019)

Multi-Agent Reinforcement Learning for Problems with Combined Individual and Team Reward. - Hassam Ullah Sheikh; Ladislau Bölöni (IJCNN, 2020)

Interaction and Behaviour Evaluation for Smart Homes: Data Collection and Analytics in the ScaledHome Project. - Matteo Mendula; Siavash Khodadadeh; Salih Safa Bacanli; Sharare Zehtabian; Hassam Ullah Sheikh; Ladislau Bölöni; Damla Turgut; Paolo Bellavista (MSWiM, 2020)

Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications. - Muhammad Zuhair Qadir; Atif Nisar Jilani; Hassam Ullah Sheikh (CoRR, 2020)

Reducing Overestimation Bias by Increasing Representation Dissimilarity in Ensemble Based Deep Q-Learning. - Hassam Ullah Sheikh; Ladislau Bölöni (CoRR, 2020)

Learning Intrinsic Symbolic Rewards in Reinforcement Learning. - Hassam Ullah Sheikh; Shauharda Khadka; Santiago Miret; Somdeb Majumdar; Mariano Phielipp (IJCNN, 2022)