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ORCIDHassam Ullah Sheikh
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2020 – today
- 2022
[c5]Hassam Ullah Sheikh, Shauharda Khadka, Santiago Miret, Somdeb Majumdar, Mariano Phielipp:
Learning Intrinsic Symbolic Rewards in Reinforcement Learning. IJCNN 2022: 1-8- 2020
- [c4]Hassam Ullah Sheikh, Ladislau Bölöni:
Multi-Agent Reinforcement Learning for Problems with Combined Individual and Team Reward. IJCNN 2020: 1-8 - [c3]Matteo Mendula
, Siavash Khodadadeh, Salih Safa Bacanli, Sharare Zehtabian, Hassam Ullah Sheikh, Ladislau Bölöni, Damla Turgut, Paolo Bellavista:
Interaction and Behaviour Evaluation for Smart Homes: Data Collection and Analytics in the ScaledHome Project. MSWiM 2020: 225-233 - [i6]Hassam Ullah Sheikh, Ladislau Bölöni:
Multi-Agent Reinforcement Learning for Problems with Combined Individual and Team Reward. CoRR abs/2003.10598 (2020) - [i5]Muhammad Zuhair Qadir, Atif Nisar Jilani, Hassam Ullah Sheikh:
Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications. CoRR abs/2006.02758 (2020) - [i4]Hassam Ullah Sheikh, Ladislau Bölöni:
Reducing Overestimation Bias by Increasing Representation Dissimilarity in Ensemble Based Deep Q-Learning. CoRR abs/2006.13823 (2020)
2010 – 2019
- 2019
- [c2]Hassam Ullah Sheikh, Ladislau Bölöni:
Emergence of Scenario-Appropriate Collaborative Behaviors for Teams of Robotic Bodyguards. AAMAS 2019: 2189-2191 - [c1]Hassam Ullah Sheikh, Mina Razghandi, Ladislau Bölöni:
Learning Distributed Cooperative Policies for Security Games via Deep Reinforcement Learning. COMPSAC (1) 2019: 489-494 - [i3]Hassam Ullah Sheikh, Ladislau Bölöni:
The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning. CoRR abs/1901.09833 (2019) - [i2]Hassam Ullah Sheikh, Ladislau Bölöni:
Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning. CoRR abs/1901.09837 (2019) - [i1]Hassam Ullah Sheikh, Ladislau Bölöni:
Universal Policies to Learn Them All. CoRR abs/1908.09184 (2019)
Coauthor Index
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