Intelligent Inference Systems Corp.

The Founder

Dr. Hamid R. Berenji

Dr. Hamid Berenji biography has been printed in the 2007 edition of Marquis Who in America
Dr. Hamid Berenji biography has been printed in the 2008 edition of Marquis WWho in the World

Education

- Ph.D., Systems Engineering, University of Southern California, Los Angeles (1986)
- M.S., Systems Engineering, University of Southern California, Los Angeles (1980)
- B.S., Systems Engineering, Iran University of Science and Technology, Tehran, Iran (1979)

Experience

4/93 to present: Chief Research Scientist,

‿Has worked on a NASA Phase II SBIR project with NASA Ames Research Center in collaboration with the Georgia Tech EE Department on the development of a prototype of Multi Agent Usage and Health Monitoring (MULTI-PHUM) with application to Monopropellant combustion.

‿Has organized a short course on Neural Networks and Intelligent Control with Professor Zurada, Professor Passino, Dr. Choi, Dr. Arabshahi, and Dr. Berenji presented to engineers from NASA Marshal in Huntsville, Alabama in June 2003.

In fiscal year 2002, a new fault diagnosis system was developed for the NASA Ames Hybrid Combustion Facility. This facility, which is managed by the Stanford University at Ames, performs tests on new rocket fuels. Also, in fiscal year 2002, a heterogeneous Robotic Colony on Mars was designed and its prototype was developed and demonstrated. In another project sponsored by the NASA Ames Research Center, Dr. Berenji and his team developed a new controller for the Shuttle Training Aircraft (STA) that improved its accuracy. This work resulted in a significant error reduction in pitch rate trajectory as tested on the ground hardware simulation facility at the NASA JSC in Ellington Field. This improvement was the result of a joint work with the NASA Shuttle Training Branch of JSC. In yet another project, Dr. Berenji and his team developed an attitude controller for the Space Shuttle in-orbit attitude control including pitch, roll, and yaw control. He also developed an automated rendezvous and docking controller for fly-around, station-keeping, V-bar and R-bar approaches in docking the space shuttle with a satellite. Dr. Berenji has originated and extended the theory of generalized reinforcement learning for intelligent control, for multi-agent learning, and using radial basis functions in reinforcement learning.

Worked on a grant from NASA Institute for Advanced Concepts (NIAC) on biologically inspired robotics. This work has resulted in a patent from the USPTO on Multi-segmented Robot.

‿Have invented a convergent Actor Critic based Reinforcement Algorithm (ACFRL) together with Dr. David Vengerov. A patent application on this invention has been obtained from the USPTO. A full journal paper of its analytical proof appeared in the IEEE transaction on Fuzzy Systems. Patented algorithm # US 6,917,925, B2, Jul 12, 2005.

Awards

Elected as IEEE Fellow, 2002,

NASA Certificate of Appreciation, for outstanding efforts in support of Ames Center of Excellence in Information Technology Strategic Plan Workshop, April 24, 1996.

‿Certificate of Recognition for the creative development of a scientific contribution which has been determined to be of significant value in the advancement of the aerospace technology program of NASA, and is entitled: Generalized Approximate Reasoning Based Intelligent Control (GARIC), April 1, 1999.

‿Certificate of Appreciation as a member of the Automation Sciences Research Dedication Team. This certificate is hereby given in appreciation for your hard work, energy, and enthusiasm given so generously to help make the ASRF Dedication event of January 31, 1992, an outstanding success. NASA Ames Research Center is grateful for your support.

‿Contractor Certificate of Excellence, October 22, 1998.

‿Certificate of Appreciation awarded in recognition of outstanding support and significant contribution to the 1996 Ames Research Center NASA Scholars Summer Internship Program From May, 1996 to September, 1996.

‿NASA Group Achievement Award to Ames Community Day Open House Team for outstanding teamwork and dedication in planning and executing the Community Day Open House within a six-month period and attracting 220,000 visitors to Ames, May 1, 1998.

‿Winner of the 1999 NASA Space Act award.

‿NASA Certificate of Appreciation 1992, 1996, and 1998

‿Winner of NASA Ames Director's Discretionary Fund, 1988.

‿Winner, best session paper award in American Control Conferences (ACC-1987, 1993)

‿Winner of a NSF grant to the second NSF sponsored workshop on Neuro-Control, 1991.

Publications

‿Berenji, H.R.,UAV Training, World Conference on Soft Computing, San Francisco,CA 2011.

‿Berenji, H. R., SBIR Phase I Final Report of the Air Force SBIR (207), 2011.

‿Berenji, H. R., SBIR Phase I Final Report of the Air Force SBIR.( 208), 2011.

‿Berenji, HR., M. Jmshidi, Fuzzy Reinforcement Learning In System of Systems, FUZZ-IEEE, Taiwan, June 2011.

‿Berenji, H. R., A tribute to Lotfi Zadeh on his 90th Birthday, Scientifica Iranica, 2011.

‿Berenji, H. R., A tribute to Lotfi Zadeh on his 90th Birthday, FikretAliev, 2011.

‿Berenji, H.R., Maryam Naghibzadeh, Fuzzy Reinforcement Learning for System Of Systems (SOS), Space Systems, Pasadena, CA, 2009.

‿H. Berenji, Y. Wang, “Case-Based Reasoning for Fault Diagnosis and Prognosis‿ FUZZ-IEEE, Vancouver, Canada, July 2006.

‿H. Berenji, Y. Wang, “Wavelet Neural Networks for Fault Diagnosis and Prognosis‿ FUZZ-IEEE, Vancouver, Canada, July 2006.

‿H. Berenji, Y. Wang, A. Saxena, “Dynamic Case Based Reasoning in Fault Diagnostics and Prognostics‿ FUZZ-IEEE, Reno, May 2005

‿H. Berenji, Y. Wang, D. Vengerov, R. Langari and M. Jamshidi, “Using Gated Experts in Fault Diagnosis and Prognosis‿ FUZZ-IEEE, Budapest, Hungary, July 2004.

‿Hamid R. Berenji, Jayesh Ametha, and David Vengerov, Inductive Learning for Fault diagnosis, the 12th IEEE International Conference on Fuzzy Systems , 2003

‿Hamid R. Berenji, David Vengerov, and Jayesh Ametha , Perception based Reinforcement Learning for Sensor Allocation in Unmanned Aerial Vehicles, the 12th IEEE International Conference on Fuzzy Systems, 2003.

‿David A. Vengerov, Nicholas Bambos, Hamid R. Berenji. Adaptive Learning Scheme for Power Control in Wireless Networks. In Proceedings of the 2002 Fall Vehicular Technology Conference (VTC).

‿David A. Vengerov, Hamid R. Berenji, Alexander B. Vengerov. (2002) Emergent Coordination among Fuzzy Reinforcement Learning Agents. A book chapter in Soft Computing Agents: A New Perspective for Dynamic Information Systems, published in the International Series "Frontiers in Artificial Intelligence and Application" by IOS Press.

‿Berenji, Hamid R. and David Vengerov., On Convergence of Fuzzy Reinforcement Learning. Accepted to appear in IEEE Transactions on Fuzzy Systems, 2002 [Presents the first ever analytical proof of Convergence of FRL].

‿David A. Vengerov, Nicholas Bambos and Hamid R. Berenji (2002), In Proceedings of the First Annual Symposium on Autonomous Intelligent Networks and Systems, UCLA, May 8-9, 2002.

‿Hamid R. Berenji, Jayesh Ametha, and David Vengerov, Heterogeneous Robotic Colonies on Mars, Robosphere 2002, November 2002, pp.: 51-54, NASA Ames Research Center, CA.

‿David A. Vengerov, Hamid R. Berenji (2002) Using Fuzzy Reinforcement Learning for Power Control in Wireless Transmitters, In proceedings of the 11th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE '02), pp. 797-802.

‿David A. Vengerov, Hamid R. Berenji, Alexander B. Vengerov (2002) Adaptive Coordination Among Fuzzy Reinforcement Learning Agents Performing Distributed Dynamic Load Balancing, In proceedings of the 11th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE '02), pp. 179-184.

‿Berenji, H., Saraf, S., Chang, P. and Swanson, S., 2001, Pitch Control of the Space Shuttle Training Aircraft, IEEE Transactions on Control Systems Technology, pp. 542-551, 2001.

‿Berenji, H., Fuzzy Reinforcement Learning and the Internet with Applications in Power Management of Wireless Networks, 2001 BISC Int. Workshop on Fuzzy Logic and the Internet, Berkeley, CA.

‿Berenji, H.R. and D. Vengerov, Coonvergent Actor Critic-based Fuzzy Reinforcement Learning Apparatus and Method, US patent 6,917,925 B2, Filed Dec. 21, 2001.

‿Berenji, Hamid R. and Vengerov, David. (2000) Advantages of Cooperation Between Reinforcement Learning Agents in Difficult Stochastic Problems. In proceedings of the 9th IEEE International Conference on Fuzzy Systems, 2000.

‿Berenji, Hamid R. and Vengerov, David. (2000) Biomorphic Reinforcement Learning Agents, NASA/DOD workshop on Bio-inspired Engineering for Exploration Systems (BEES 2000), JPL, December 4-6, 2000.

‿Berenji, Hamid R. and Vengerov, David. (2000) Biomorphic Reinforcement Learning Agents, NASA/DOD workshop on Bio-inspired Engineering for Exploration Systems (BEES 2000), JPL, December 4-6, 2000.

‿Berenji, H.R. and D. Vengerov, Cooperation and Coordination between teams of Fuzzy Reinforcement Agents, FUZZ-IEEE, Seoul, Korea, FUZZ-IEEE, Seoul, Korea, 1999.

‿Berenji HR & Saraf S. (1998) Neuro-fuzzy control of the shuttle training aircraft. Proceedings of World Congress of Automation, Anchorage, Alaska, pp622-627.

‿Berenji, H.R. and P. Khedkar, Using Fuzzy Logic for Performance Evaluation in Reinforcement Learning, International Journal of Approximate Reasoning, 1998.

‿Berenji, H.R., Learning and Tuning of Fuzzy Rules, Handbook of Fuzzy Modeling and Control, Volume 6, M. Sugeno, H. Nguyen (eds.), 1998, Kluwer Academic

‿Berenji, H.R., Reinforcement Learning for Feedback Control, AAAI Symposium on Application of Reinforcement Learning, Palo Alto, CA, March 1998.

‿Berenji, H.R. and S. Saraf, Competition and Collaboration among Fuzzy Reinforcement Learning Agents, Seventh IEEE International conference on Fuzzy Systems, Anchorage, Alaska, May 1998.

‿Berenji, H.R. and P.W. Chang and V. Chu and S. Saraf, An Environment for Computational Intelligence, NASA SBIR phase 2 final report, 1997.

‿R. Jacobs and H.R. Berenji, Learning and Tuning Human Stance Control Through Reinforcements, Neural Control of Movements (NCM) meeting, Cancun, Mexico, April 8-14, 1997.

‿Berenji, H.R. and P.W. Chang and V. Chu and S. Saraf, An Environment for Computational Intelligence, NASA SBIR phase 2 final report, 1997.

‿H.R. Berenji, “Collaborative fuzzy reinforcement learning agents‿ International Fuzzy Systems Association World Congress, 1997.

‿Berenji H.R, Chang P-W & Swanson S (1997) Refining the shuttle training aircraft. Proceedings of 6th International conference on fuzzy systems, Barcelona, Spain, pp677-682.\

‿Berenji, H.R., Computationnal intelligence and soft Computing for Space Applications, Aerospace Magazine, August 1996.

‿Berenji, H.R. and P.S. Khedkar and A. Malkani, Refining Linear Fuzzy Rules by Reinforcement Learning, Fifth IEEE International conference on Fuzzy Systems, New Orleans, Louisiana, September 1996.

‿Berenji, H.R., Reinforcement Learning in Fuzzy Dynamic Programming, Fifth IEEE International conference on Fuzzy Systems, New Orleans, Louisiana, September 1996.

‿Berenji, H.R. and E.H. Ruspini, Experiments in Multi-objective Fuzzy Control of Hybrid Automotive Engines, Fifth IEEE International conference on Fuzzy Systems, New Orleans, Louisiana, September 1996.

‿Berenji, H.R., Fuzzy Q-Learning for Generalization of Reinforcement Learning, Fifth IEEE International conference on Fuzzy Systems, New Orleans, Louisiana, pp. 2208-2214, September 1996.

‿Berenji, H.R., Adaptive Fuzzy Systems in Computational Intelligence, workshop on Computational Intelligence and Its Impact on Design/Fabrication and Operation of Future High-Performance Engineering Systems, Hampton, VA, 1995.

‿Berenji, H.R., Fuzzy Logic Systems in Computational Intelligence, WESCON, San Francisco, CA, 1995

‿Berenji, H.R. and E. H. Ruspini, Automated Controller Elicitation and Refinement for Power Trains of Hybrid Electric Vehicles, 4th IEEE Conference on Control Applications, Albany, New York, 329-334, September 1995.

‿Berenji, H.R. and A. Malkani and C. Copeland, Tether Control Using Fuzzy Reinforcement Learning, Fourth IEEE International conference on Fuzzy Systems, Yokohama, Japan, March 1995.

‿Berenji, H.R., P.P. Bonissone, J.C. Bezdek, D. Dubois, R. Kruse, H. Prade, Ph. Smets, and R.R. Yager, A Reply to the Paradoxial Success of Fuzzy Logic, AI Magazine, volume: 15(1), pages: 6-8, Spring 1994.

‿Berenji, H.R., Fuzzy Q-Learning: A New Approach for Fuzzy Dynamic Programming Problems, Third IEEE International conference on Fuzzy Systems, Orlando, FL, June 1994.

‿Berenji, H.R., Fuzzy Reinforcement Learning and Dynamic Programming, Fuzzy Logic in Artificial Intelligence, International joint Conference on Artificial Intelligence, workshop, editedby: A.L. Ralescu, pages: 1-9, Springer-Verlag, France, 1994.

‿Berenji, H.R., On Elkan's Paradoxes about the Success of Fuzzy Logic, IEEE Expert, pages: 1-49, August 1994.

‿Berenji, H.R., Fuzzy Systems that Can Learn, Computational Intelligence Imitating Life, J.M. Zurada, R.J. Marks II, C.J. Robinson, pp. 23-30, 1994, IEEE Press.

‿Berenji, H.R. and S. Malyshev, A Fuzzy Reinforcement Learning System Based on Genetic Algorithm, NASA SBIR phase 1 final report, July 1994.

‿Berenji, H.R., An Architecture for Designing Fuzzy Controllers using Neural Networks, Readings in Fuzzy Sets for Intelligent Systems, Edited by: D. Dubois, Henri Prade, and Ronald Yager, pages: 368-380, Morgan Kaufmann, 1993.

‿Berenji, H.R., Refining Fuzzy Controllers with Machine Learning, Fourth National Technology Transfer Conference, 3-6, Anaheim, December 1993

‿Berenji, H. R. and P.S. Khedkar , Adaptive Fuzzy Control with Reinforcement Learning , American Control Conference, San Francisco, CA, June 1993.

‿Berenji, H.R., R.N Lea, Y. Jani, A. Malkani, J. Hoblit, A Learning Fuzzy Logic Controller for the Space Shuttle's Orbital Operations, AI Research Branch, FIA-92-30, October 1993.

‿Berenji, H.R. and P. Khedkar , Clustering in Product Space for Fuzzy Inference, Second IEEE International conference on Fuzzy Systems , 1402-1407, San Francisco, CA , March 1993.

‿Berenji, H.R., Fuzzy Reinforcement Learning and Dynamic Programming, International joint Conference on Artificial Intelligence, workshop on Fuzzy Logic Control, Chambery, France, August 1993.

‿Berenji, H.R., Neural Networks for Fuzzy Logic Inference, Second IEEE International conference on Fuzzy Systems, San Francisco, CA, March 1993.

‿P. Khedkar and H.R. Berenji, Generating Fuzzy Rules with Linear Consequents from Data, World Congress on Neural Networks, II, 18-21, Portland, Oregon, July 1993.

‿Berenji, H.R., Fuzzy and Neural Control, in: An Introduction to Intelligent an Autonomous Control, Antsaklis, P.J. and K. M. Passino (eds.), 1992.

‿Berenji, H. R., Khedkar, Pratap, Using Fuzzy Logic for Performance evaluation in Reinforcement Learning, AI Research Branch, FIA-92-28, July 1992.

‿Berenji, H.R. and P. Khedkar, Fuzzy Rules for Guiding Reinforcement Learning, IPMU, Palma de Mallorca, Spain, July 1992.

‿Berenji, H.R., Fuzzy and Neural Control, AI Research Branch, NASA Ames Research Center, no.:FIA-92-19, May 1992.

‿Berenji, H.R. and P. Khedkar, Learning and Tuning Fuzzy Logic Controllers through Reinforcements, vol. 3, no.5, IEEE Transactions on Neural Networks, 1992.

‿Langari, R. and H.R. Berenji, Fuzzy Logic in Control Engineering, editors: David White and Donald Sofege, Handbook of Intelligent Control, Van Nostrand, 1992.

‿H. Berenji, An Architecture for Designing Fuzzy Controllers using Neural Networks, International Journal of Approximate Reasoning, volume 6, no. 2, pp. 267-292, Feb. 1992.

‿Berenji, H.R. and P. Khedkar, Fuzzy Inference with Reinforcement Learning, AI Research Branch, NASA Ames Research Center, no.:FIA-92-2, January 1992.

‿Langari, R. and H.R. Berenji, Fuzzy Logic in Control Engineering, editors: David White and Donald Sofege, Handbook of Intelligent Control, Van Nostrand, 1992.

‿Berenji, H.R. and P. Khedkar, Structure Identification in Fuzzy Inference Using Reinforcement Learning, Third International Joint Technology Workshop on Neural Networks and Fuzzy Logic, June 1992

‿Berenji, H.R., Y.Y. Chen, C.C. Lee, J.S. Jang and S. Murugesan, A Hierarchical Approach to Designing Approximate Reasoning-Based Controllers for Dynamic Physical Systems, Uncertainty in Artificial Intelligence: Volume VI, in the series Machine Intelligence and Pattern Recognition, Edited by: P.P. Bonissone, M. Henrion, L.N. Kanal, and J. Lemmer, pages: 331-343, Elsevier, North-Holland, 1991.

‿Berenji, H. R., An Introduction to Fuzzy Logic Applications in Intelligent Systems, in: Fuzzy Logic Controllers, Kluwer Academic Publishers, pages:69-96, edited by: Yager, R. R. and L.A. Zadeh, 1991.

‿Berenji, H. R., On Integration of Reinforcement Learning and Approximate Reasoning, 30th IEEE Conference on Decision and Control, Brighton, England, pp. 1900-1904, 1991.

‿Berenji, H. and Y. Jani and R. Lea, Approximate Reasoning-based Learning and Control for Proximity Operations and Docking in Space, AIAA Guidance, Navigation and Control Conference, New Orleans, Louisiana, August 12-14, 1991.

‿Berenji, H. R., Artificial Neural Networks and Approximate Reasoning for Intelligent Control in Space, Proceedings of the American Control Conference, IEEE, Boston, Massachusetts, 1075-1080, 1991

‿H. Berenji, Response to Saffiotti's An AI view of the treatment of uncertainty, Knowledge Engineering Reviews, vol. 3(1), pp. 59-86, 1988.

‿H. Berenji, B. Khoshnevis, Use of Artificial Intelligence in Automated Process Planning, Journal of Computers in Mechanical Engineering, vol. 5, no. 2, pp. 47-55, 1986.

‿Berenji, H., Strategy Learning in Fuzzy Logic Control, North American Fuzzy Information Processing Society Workshop, Columbia, Missourri, pp. 301-306, 1991.

‿Berenji, H. R., Refinement of Approximate Reasoning-based Controllers by Reinforcement Learning, Proceedings of the Eighth International Workshop on Machine Learning, Morgan Kaufmann, San Mateo, CA, pp. 475-479, 1991.

‿T. Whalen, H. Berenji, Actions as Evidence: Multiple Epistemic Agents Acting Under Uncertainty, Second ACM Annual Conference on AI, Simulation and Planning in High Autonomy Systems, Cocoa Beach, Florida, April 1991.

‿H. Berenji, Neural Networks and Fuzzy Logic in Intelligent Control in proceedings of the Fifth IEEE International Symposium on Intelligent Control, Philadelphia, 1990.

‿H. Berenji, Machine Learning in Fuzzy Control, International Conference on Fuzzy Logic & Neural Networks, Iizuka, Japan, 1990.

‿H. Berenji, An Architecture for Designing Fuzzy Logic Controllers using Neural Networks, www.poloralphlaurenaustralia.biz second joint technology workshop on neural networks and fuzzy logic, pp. 1-29, Houston, 1990

‿H. Berenji, Y.Y. Chen, R. Yager, Using New Aggregation Operators in Rule-Based Intelligent Control, 29th IEEE Conference on Decision and Control, 1990.

‿H. Berenji, Y.Y Chen, C.C. Lee, J.S. Jang, S. Murugesan, A Hierarchical Approach to Designing Approximate Reasoning-Based Controllers for Dynamic Physical Systems, Sixth Conference on Uncertainty in AI, Boston, MA, pp. 362-369, 1990.

‿Berenji, H.R., NASA/ARC Proposed Training in Intelligent Control, Workshop on Fuzzy Control Systems and Space Station Applications, 1990, 99-107.

‿C. C. Lee, H. Berenji, An Intelligent Controller Based On Approximate Reasoning and Reinforcement Learning, proceedings of the Fourth IEEE International Symposium on Intelligent Control, pp. 200-205, Albany, 1989.

‿Ralescu, A., and H. Berenji, Integrating Structured Knowledge and Management of Uncertainty in Intelligent Systems, International Joint Conference on Artificial Intelligence (IJCAI) workshop on Conceptual Graphs, Detroit, 1989.

‿H. Berenji, Y.Y. Chen, C.C. Lee, S. Murugesan, J.S. Jang, An experiment-based comparative study on Fuzzy Control, American Control Conference, Pittsburgh, Pennsylvania, pp. 2751-2753, 1989.

‿Berenji, H. R., Treatment of Uncertainty in Artificial Intelligence, in: Machine Intelligence for Aerospace Robotics, American Institute of Aeronautics and Astronautic, Inc., pages: 233-247, vol. 115, edited by: Heer, E. and H. Lum, 1988.

‿H. Berenji, An Integrated Approach to Reasoning under Uncertainty, proceeding of NASA Ames second AI Forum, Palo Alto, pp. 199-211, December 1987.

‿H. Berenji, H. Lum, Jr., Application of Plausible Reasoning to AI-Based Control Systems, Proceedings of the American Control Conference, Minneapolis, MN, pp 1655-1661, June 1987.

‿H.R. Berenji, Manufacturing Generative Process Planning with Relational Productions System in Artificial Intelligence, Ph.D. Dissertation, University of Southern California, 1986.

‿Berenji, H. R. and B. Khoshnevis, Manufacturing Generative Process Planning with Relational Production System, IEEE conference on Systems, Man, and Cybernetics,Tuscon, AZ, November 1985

‿Berenji, H. R. and B. Khoshnevis and E. Heer, AI-Based Generative Process Planning, Second meeting of the Southern California Artificial Intelligence Society, Los Angeles, CA, April 1985.

‿Berenji, H. R. and B. Khoshnevis, An Expert Process Planning System, TIMS/ORSA joint National Meeting, Boston, MA, April 1985

‿Torres, J.F., H.J. Payne, A. Halati, B. Mikhalkin and H. Berenji and H. Atabaki, Freeway Control and Management for Energy Conservation, Department of Energy, FHWA/RD-82/058, September 1982 .