Murad Abu-Khalaf

Reinforcement Learning · 2005–2015

A researcher in the Science corpus: 6 papers; trusts 9 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 14 citations into it
• Computational Theory and Mathematics — 10 citations into it; #664 of 12,182 by trust here, #925 by citations
• Control and Systems Engineering — 10 citations into it; #907 of 8,257 by trust here, #2,376 by citations
• Artificial Intelligence — 6 citations into it; #7,560 of 35,345 by trust here, #13,760 by citations
• Electrical and Electronic Engineering — 6 citations into it; #2,269 of 16,539 by trust here, #7,062 by citations

Whom Murad Abu-Khalaf trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Dimitri P. Bertsekas
2. Paul J. Werbos
3. Richard S. Sutton
4. Andrew Barto
5. Frank L. Lewis
6. Victor M. Becerra
7. Kurt Hornik
8. Kok Lay Teo
9. Asma Al-Tamimi

Who trusts Murad Abu-Khalaf overall

1. Frank L. Lewis
2. Derong Liu
3. Kyriakos G. Vamvoudakis
4. Hamidreza Modares
5. Huaguang Zhang
6. Ding Wang
7. Qinglai Wei
8. Draguna L. Vrabie
9. Shubhendu Bhasin
10. Lili Cui

Papers from Murad Abu-Khalaf's perspective

Ordered by how strongly the researchers Murad Abu-Khalaf trusts endorse each paper. Same corpus, a different order for every researcher.

1. Dynamic Programming and Markov Processes
2. Learning from delayed rewards
3. Neuronlike adaptive elements that can solve difficult learning control problems
4. A Menu of Designs for Reinforcement Learning Over Time
5. Neural Network Control Of Robot Manipulators And Non-Linear Systems
6. Approximating Integrals Via Monte Carlo and Deterministic Methods
7. Solving Hamilton-Jacobi-Bellman equations by a modified method of characteristics
8. Online learning control by association and reinforcement
9. Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks
10. Dynamic Programming: Deterministic and Stochastic Models

Their papers

• Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach (2005) — 1,307 citations
• Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof (2008) — 1,009 citations
• Model-free Q-learning designs for discrete-time zero-sum games with application to H-infinity control (2007) — 554 citations
• Adaptive optimal control for continuous-time linear systems based on policy iteration (2009) — 916 citations
• IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015) — 46 citations
• Necessary and Sufficient Conditions for H-∞ Static Output-Feedback Control (2006) — 110 citations