Alan D. Blair

发表

Why did TD-Gammon Work?

Jordan B. Pollack, Alan D. Blair, J. Pollack, 1996, NIPS.

Incremental training of first order recurrent neural networks to predict a context-sensitive language

Stephan K. Chalup, Alan D. Blair, A. Blair, 2003, Neural Networks.

Motion Control for Fast Mobile Robots: A Trajectory-Based Approach

Ed Kazmierczak, Alan D. Blair, Andrew Howard, 2000 .

Evolving Learnable Languages

Janet Wiles, Alan D. Blair, Bradley Tonkes, 1999, NIPS.

Evolving Plastic Neural Networks for Online Learning: Review and Future Directions

Alan D. Blair, Oliver J. Coleman, A. Blair, 2012, Australasian Conference on Artificial Intelligence.

What Makes a Good Co-Evolutionary Learning Environment?

Jordan B. Pollack, Alan D. Blair, J. Pollack, 1997 .

Getting the Job Done in a Hostile Environment

Steven Versteeg, Alan D. Blair, S. Versteeg, 2001, Australian Joint Conference on Artificial Intelligence.

Models of Brains: What Should We Borrow From Biology?

Alan D. Blair, Oliver J. Coleman, A. Blair, 2013, AAAI Fall Symposia.

Exploitation and peacekeeping: introducing more sophisticated interactions to the iterated prisoner's dilemma

Toby Ord, Alan D. Blair, Toby Ord, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

Co-Evolution in the Successful Learning of Backgammon Strategy

Jordan B. Pollack, Alan D. Blair, J. Pollack, 1998, Machine Learning.

Analysis of Dynamical Recognizers

Jordan B. Pollack, Alan D. Blair, J. Pollack, 1997, Neural Computation.

Inductive Bias in Context-Free Language Learning

Janet Wiles, Alan D. Blair, Brad Tonkes, 1998 .

Automated generation of environments to test the general learning capabilities of AI agents

Jeff Clune, Alan D. Blair, Oliver J. Coleman, 2014, GECCO.

Quasi-Orthogonal Maps for Dynamic Language Recognition

Jordan B. Pollack, Alan D. Blair, 1997, ICONIP.

Decentralised data fusion with exponentials of polynomials

Alan D. Blair, Bradley Tonkes, 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Learning to Predict the Phonological Structure of English Loanwords in Japanese

John Ingram, Alan D. Blair, 2004, Applied Intelligence.

Software for Analysing Recurrent Neural Nets That Learn to Predict Non-regular Languages

Stephan K. Chalup, Alan D. Blair, A. Blair, 2002, ICGI.

Learning the Dynamics of Embedded Clauses

Mikael Bodén, Alan D. Blair, A. Blair, 2003, Applied Intelligence.

Co-evolution, Determinism and Robustness

Elizabeth Sklar, Pablo Funes, Alan D. Blair, 1998, SEAL.

A Paradox of Neural Encoders and Decoders or Why Don't We Talk Backwards?

Janet Wiles, Alan D. Blair, Bradley Tonkes, 1998, SEAL.

An Abstract Deep Network for Image Classification

Alan D. Blair, Anthony Knittel, A. Blair, 2012, Australasian Conference on Artificial Intelligence.

Hill Climbing in Recurrent Neural Networks for Learning the abc Language

Stephan K. Chalup, Alan D. Blair, 2008 .

Artificial Life and Computational Intelligence: First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings

Stephan K. Chalup, Alan D. Blair, Marcus Randall, 2014 .

Sparse, guided feature connections in an Abstract Deep Network pdf

Alan D. Blair, Anthony Knittel, 2014, ArXiv.

Artificial Life and Computational Intelligence

Stephan K. Chalup, Alan D. Blair, Marcus Randall, 2015, Lecture Notes in Computer Science.

On the ability of recurrent nets to learn deeply embedded structures

Janet Wiles, Mikael Bodén, Alan D. Blair, 1999, IJCAI 1999.

Exploring evolutionary learning in a simulated hockey environment

Elizabeth Sklar, Alan D. Blair, E. Sklar, 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

Loanword formation: a neural network approach

John Ingram, Alan D. Blair, 1998, SIGPHON@COLING/ACL.

Guest Editorial Special Issue: Evolutionary Computation and Games

R. Miikkulainen, D. B. Fogel, Alan D. Blair, 2005 .

Training Intelligent Agents Using Human Data Collected on the Internet

Elizabeth Sklar, Jordan B. Pollack, Alan D. Blair, 2001 .

Training intelligent agents using human internet data

Elizabeth Sklar, Jordan B. Pollack, Pablo Funes, 1999 .

First Order Recurrent Neural Networks Learn To Predict A Mildly Context-Sensitive Language

Stephan K. Chalup, Alan D. Blair, A. Blair, 2000 .

Incremental Learning for RNNs: How Does it Affect Performance and Hidden Unit Activation?

Stephan K. Chalup, Alan D. Blair, A. Blair, 2003 .

Learning to predict a context-free language: analysis of dynamics in recurrent hidden units

Janet Wiles, Mikael Bodén, Alan D. Blair, 1999 .

Coarse and fine learning in deep networks

Alan D. Blair, Anthony Knittel, A. Blair, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Coevolution of a Backgammon Player

Jordan B. Pollack, Alan D. Blair, J. Pollack, 1996 .

Transgenic Evolution for Classification Tasks with HERCL

Alan D. Blair, A. Blair, 2015, ACALCI.

Co-evolutionary Learning : Machines and Humans Schooling Together

Elizabeth Sklar, Jordan B. Pollack, Alan D. Blair, 1998 .

Scaling-up RAAMs

Alan D. Blair, A. Blair, 1997 .

Deriving Sensor Models and Non-Linear Filtering for Exponentials of Polynomials

Alan D. Blair, Bradley Tonkes, A. Blair, 2007 .