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Faculty Profile Last Modified Time: 09:55:07 AM Tue, 1 Sep 2009   Contact Information Dr. Manfred Huber Associated Profiles  Associate Professor-Computer Science & Engineering     Arlington, TX 76019     Mail Box: 19015, GACB, Room No.: 114    huber@cse.uta.edu     22345    Faculty Home Page    Personal Home Page    Autonomous Robot Systems, Sensor driven robotics Machine learning, Development of Intelligent behavior    Associated Profiles Professional Preparation Publications Appointments Teaching  Professional Preparation  Degree Major Institution Year  Ph.D. Computer Science University of Massachusetts 2000  M.S. Computer Science University of Massachusetts 1993  'Vordiplom' Computer Science University of Karlsruhe 1990  Publications   Category  All  Type AllOtherPeer reviewedConference paper Publications per page    1  2 3 4 5 6 7 8 9 10    Year Publication   Type 2005 Published Asadi M, Huber M (2005), Accelerating Action Dependent Hierarchical Reinforcement Learning Through Autonomous Subgoal Discovery, To appear in ICML 2005 Workshop on Rich Representations for Reinforcement Learning, Bonn, Germany. © 2005 ACM Conference paper 2005 Published Asadi M, Huber M (2005), Hierarchical State Abstraction with Subgoal Discovery Using Learned Policies, In Prodeedings of the International Conference on Machine Learning; Models, Technologies and Applications, Las Vegas, NV. © 2005 LPL Conference paper 2005 Published Rajendran S, Huber M (2005), Learning Task-Specific Sensing, Control and Memory Policies, International Journal on Artificial Intelligence ToolsVol. 14, No. 1-2, pp. 303-328. © 2005 World Scientific Publishing Conference paper 2005 Published Elliott F, Huber M (2005), Learning Macros with an Enhanced LZ78 Algorithm, In Prodeedings of the 18th International FLAIRS Conference, Clearwater Beach, FL. © 2005 AAAI Conference paper 2005 Published Grupen RA , Huber M (2005), A Framework for the Development of Robot Behavior, AAAI Spring Symposium on Developmental Robotics, Stanford, CA. © 2005 LPL Conference paper  Appointments Duration Rank Department / School College / Office University / Company 2006-present Associate Professor Computer Science College of Engineering University of Texas at Arlington 2000-2006 Assistant Professor Computer Science College of Engineering Univeristy of Texas at Arlington 1999-2000 Visiting Assistant Professor Computer Science College of Engineering University of Texas at Arlington  Teaching   CSE 5361-001 - Artificial Intelligence II Spring 2009 This course introduces and applies the AI techniques necessary for an agent to act intelligently in the ``real'' world. Techniques include uncertainty reasoning, learning, natural language processing, vision and speech processing. Basic AI techniques will be reviewed in the context of the Java programming language which will be used for implementing the more advanced techniques. Emphasis will be on implementation and experimentation with the goal of building robust intelligent agents. Download Syllabus (13.01KB. This syllabus was uploaded Tuesday 20th, January 2009 10:22:14 AM and is subject to change.) AI II [ Show Additional Information ] Students in this course will be introduced to modern artificial intelligence techniques which enable computer systems to interact with the world and the computer user. This permits efficient decision making by computer programs and is therefore an essential component of future, interactive computer software. Students successfully completing this course will be able to apply a variety of techniques for the design of intelligent agents to address complex problems. Contact Information GACB, #114  Hours: MW 1:00-2:00, W4:00-5:00 Phone: 22345  Email: huber@cse.uta.edu   CSE 6369-001 - Multiagent Systems Fall 2009 Multiagent systems has emerged as an important research area with applications in many fields of computer science, including artificial intelligence, e-commerce, sensor networks, distributed computing and information retrieval, information security, and robotics. In multiagent systems, multiple autonomous entities with their own objectives have to interact and make decisions. This course explores techniques for the modeling, design, decision making, and communication in these systems. While the course will focus on frameworks, methodologies, and algorithms, it will investigate (and illustrate) them in the context of a wide range of application areas, including multi-robot systems, distributed scheduling and resource allocation, sensor networks, distributed information extraction, and network security. Download Syllabus (60.6KB. This syllabus was uploaded Tuesday 01st, September 2009 09:55:07 AM and is subject to change.) Multiagent Systems Contact Information GACB, #114  Hours: MW 8:20-9:20, Tu 3:00-4:00 Phone: 22345  Email: huber@cse.uta.edu For the Official List of Courses for registration, please visit MyMav - Schedule of Classes