Neural Networkshttp://www.cs.utexas.edu/users/nn/
Director: Risto Miikkulainen
Our research concentrates on understanding and generating intelligent behavior with artificial neural networks. On one hand, the goal is to better understand human information processing, that is, how intelligent behavior in humans arises from neural network mechanisms. On the other, the research aims at building more intelligent artificial systems. Our approach is to develop algorithms and architectures that explicitly represent and make use of the structure in the task, such as schemas, subgoals, and modularity. This way it is possible to build neural network models of more complex behavior than is possible with traditional uniform network architectures. For example, high-level processes such as schema learning, sentence understanding, and game playing can be implemented with modular neural networks, and such systems can often be more efficient and cognitively valid than traditional models.
Members
- Adrian Agogino
- Nora E. Aguirre-Celis
- Matt Alden
- Timothy Andersen
- Erkin Bahceci
- James A. Bednar
- Julian Bishop
- Yonatan Bisk
- Justine Blackmore
- Joe Bruce
- Joseph Bruce
- Bobby Bryant
- Li-Chiu Chang
- Harold H. Chaput
- Chun-Chi Chen
- Yoonsuck Choe
- Alex Conradie
- Ryan Cornelius
- Thomas D'Silva
- Judah De Paula
- Nirav S. Desai
- James Fan
- Igor Farkas
- Peggy Fidelman
- Brad Fullmer
- Aliza Gold
- Faustino Gomez
- Aravind Gowrisankar
- Uli Grasemann
- Brian Greer
- Todd Greer
- Andrea Haessley
- Nabil Hewahi
- Jon Hilbert
- Adam Hilss
- Michael Howe
- Daniel L. James
- Stefanie Jegelka
- Elizabeth C. Kaczmarczyk
- Thomas W. Karjala
- Igor Karpov
- Rohit Jaivant Kate
- Amol Kelkar
- Nate Kohl
- Shailesh Kumar
- Wee Kheng Leow
- Daniel Lessin
- Alan Lockett
- Alex Lubberts
- Marshall R. Mayberry, III
- Paul H. McQuesten
- Risto Miikkulainen
- Mark Moll
- German Monroy
- David E. Moriarty
- Brita Munsinger
- Enrique Muro
- Andres Santiago Perez-Bergquist
- Daniel Polani
- John Prior
- Jefferson Provost
- Melissa Redford
- Joseph Reisinger
- Norman Richards
- Jake Ryan
- Manish Saggar
- Juergen Schmidhuber
- Jacob Schrum
- Yaron Silberman
- Bryan Silverthorn
- Joseph Sirosh
- Yiu Fai Sit
- Ed Son
- Ken Stanley
- Rupert Tang
- Rick Tanney
- Tal Tversky
- Vinod Valsalam
- Austin Waters
- Gert Westermann
- Paul Williams
- Hong Yeh
- Chern Han Yong
- Dagmar (Dasa) Zeithamova
Projects
- Acquisition of Intellectual Expertise
- Adaptive Packet Routing: The Confidence-Based Dual Reinforcement Q-Learning Algorithm
- CLA: The Constructivist Learning Architecture
- Computational and Behavioral Evidence for Bilingual Aphasia Rehabilitation
- Computational Maps in the Visual Cortex
- Constructing Intelligent Agents in Simulated Worlds
- Controlling a Finless Rocket Through Neuroevolution
- Controlling Chaos
- Cooperative Coevolution of Multi-Agent Systems
- Creating Melodies with Evolving Recurrent Networks
- Data Rectification for Process Control
- Diverse Behavior in Teams of Homogeneous Agents
- Dynamic Resource Allocation on a Multiprocessor Chip
- Eugenic Evolution: The EuA, EuSANE, and TEAM
- Evolving Confident Neural Networks
- Evolving Locomotion Controllers for Multilegged Robots
- Forming Text Representations with Neural Networks
- GLISSOM: Modeling Large Cortical Maps
- HFM: Hierarchical Features Maps
- IGG: Visualization with Incremental Grid Growing
- Intrusion Detection
- Learning Navigation for Personal Satellite Assistant using Neuroevolution
- Learning Schemas for Robot Perception
- Learning Word Meanings: The FGREP Method
- Leveraging Human Creativity with Machine Discovery
- LISSOM: Laterally Interconnected Self-Organizing Maps
- Marker-Based Encoding of Neural Networks
- Modeling the Emergence of Syllable Systems
- Modular Neuroevolution for Multilegged Locomotion
- Natural Deduction
- NEAT: Evolving Increasingly Complex Neural Network Topologies
- NERO: NeuroEvolving Robotic Operatives
- Neural Network Models of Schizophrenic Language
- Nonlinear, Adaptive Process Control
- On-Line Adaptation of a Signal Predistorter through Dual Reinforcement Learning
- Optimizing a Manufacturing Process
- Organization and Disorders of the Mental Lexicon: The DISLEX System
- Orientation Perception in the RF-LISSOM Model
- PGLISSOM: Perceptual Grouping in a Self-Organizing Map of Spiking Neurons
- Playing Go
- Playing Othello
- Processing Script-Based Stories: The DISCERN System
- Real-time Interactive Gaming
- Realtime Continuous Adaptive Behavior: The Rodney System
- Refinement and On-Line Adaptation of Neurocontrollers Through Particle swarming
- Robot Control
- SARDNET: Forming Maps of Sequences
- Schema-Based Object Recognition and Scene Analysis: The VISOR System
- Segmentation and Binding: the SLISSOM Model
- Self-Organization Driven by Internally-Generated Patterns
- Self-Organization in the Primary Visual Cortex: The RF-LISSOM Model
- Self-Organization of Directional Selectivity
- Semantic Disambiguation in Sentence Processing
- Semantic Effect on Episodic Associations
- SODA: Self-Organizing Distinctive State Abstraction
- Solving Non-Markov Control Tasks
- Sound System Differentiation Through Time
- Storing Information on Maps: The Trace Feature Map Model
- Structure and Capacity of Hippocampal Memory: The Convergence-Zone model
- Symbiotic Evolution: The SANE System
- Tilt Aftereffects in the RF-LISSOM Model
- Understanding Complex Sentences with the Sentence Gestalt Model
- Understanding Sentences with Relative Clauses: The SPEC System
- Utilizing Population Culture in Neuroevolution
- Vision-Driven Development of Auditory Spatial Maps
