5 citations · 8 across the 3 of their papers we have counts for
7 papers
Learning Intrinsic Symbolic Rewards in Reinforcement Learning
Hassam Sheikh, Shauharda Khadka, Santiago Miret +1
Learning effective policies for sparse objectives is a key challenge in Deep Reinforcement Learning (RL). A common approach is to design task-related dense rewards to improve task…
Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications
Muhammad Zuhair Qadir, Atif Nisar Jilani, Hassam Ullah Sheikh
Since Android has become a popular software platform for mobile devices recently; they offer almost the same functionality as personal computers. Malwares have also become a big co…
Multi-Agent Reinforcement Learning for Problems with Combined Individual and Team Reward
Hassam Ullah Sheikh, Ladislau Bölöni
Many cooperative multi-agent problems require agents to learn individual tasks while contributing to the collective success of the group. This is a challenging task for current sta…
Universal Policies to Learn Them All
Hassam Ullah Sheikh, Ladislau Bölöni
We explore a collaborative and cooperative multi-agent reinforcement learning setting where a team of reinforcement learning agents attempt to solve a single cooperative task in a…
Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning
Hassam Ullah Sheikh, Ladislau Bölöni
We are considering a scenario where a team of bodyguard robots provides physical protection to a VIP in a crowded public space. We use deep reinforcement learning to learn the poli…
The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning
Hassam Ullah Sheikh, Ladislau Bölöni
In this paper we are considering a scenario where a team of robot bodyguards are providing physical protection to a VIP in a crowded public space. We show that the problem involves…