S
Sherief Abdallah
Researcher at British University in Dubai
Publications - 74
Citations - 1637
Sherief Abdallah is an academic researcher from British University in Dubai. The author has contributed to research in topics: Reinforcement learning & Markov decision process. The author has an hindex of 21, co-authored 71 publications receiving 1380 citations. Previous affiliations of Sherief Abdallah include University of Massachusetts Amherst & University of Edinburgh.
Papers
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Journal ArticleDOI
Cooperating with machines.
Jacob W. Crandall,Mayada Oudah,Tennom,Fatimah Ishowo-Oloko,Sherief Abdallah,Sherief Abdallah,Jean-François Bonnefon,Manuel Cebrian,Azim F. Shariff,Michael A. Goodrich,Iyad Rahwan +10 more
TL;DR: An algorithm is developed that can cooperate effectively with humans when cooperation is beneficial but nontrivial, something humans are remarkably good at, and indicates that general human–machine cooperation is achievable using a non-trivial but ultimately simple set of algorithmic mechanisms.
Proceedings ArticleDOI
Multiagent reinforcement learning and self-organization in a network of agents
Sherief Abdallah,Victor Lesser +1 more
TL;DR: This work develops a novel self-organization mechanism that not only allows agents toSelf-organize the underlying network during the learning process, but also uses information from learning to guide the self- Organization process.
Journal ArticleDOI
A multiagent reinforcement learning algorithm with non-linear dynamics
Sherief Abdallah,Victor Lesser +1 more
TL;DR: A new MARL algorithm called the Weighted Policy Learner (WPL), which allows agents to reach a Nash Equilibrium (NE) in benchmark 2-player-2-action games with minimum knowledge and outperforms the state-of-the-art algorithms in a more realistic setting of 100 agents interacting and learning concurrently.
Proceedings ArticleDOI
Organization-based cooperative coalition formation
Sherief Abdallah,Victor Lesser +1 more
TL;DR: This work presents a novel distributed algorithm that returns a solution in polynomial time and the quality of the returned solution increases as agents gain more experience.
Journal ArticleDOI
Behavioral experiments for assessing the abstract argumentation semantics of reinstatement.
Iyad Rahwan,Iyad Rahwan,Iyad Rahwan,Mohammed Iqbal Madakkatel,Jean-François Bonnefon,Ruqiyabi Naz Awan,Sherief Abdallah,Sherief Abdallah +7 more
TL;DR: This work advocates a complementary, descriptive-experimental method, based on the collection of behavioral data about the way human reasoners handle these critical cases of reinstatement, which shows that floating reinstatement yields comparable effects to that of simple reinstatement.