MastersWork.AnthonysReferences History
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Changed lines 5-6 from:
* B?ck, T., U. Hammel, et al. (1997). "Evolutionary Computation: Comments On The History and Current State." IEEE Transactions on Evolutionary Computation 1(1):
3-17.
3-17.
to:
* B?ck, T., U. Hammel, et al. (1997). "Evolutionary Computation: Comments On The History and Current State." IEEE Transactions on Evolutionary Computation 1(1): 3-17.
Changed lines 7-80 from:
Genetic Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Chalmers, D. J. (1991). The Evolution of Learning: An Experiment in
Genetic Connectionism.
Proceedings of the 1990 Connectionist Models Summer School.
* Cliff, D., I. Harvey, et al. (1992). Incremantal Evolution of Neural
Network Architectures for
Adaptive Behaviour, School of Cognitive and Computing Sciences.
University of Sussex.
* Cliff, D., I. Harvey, et al. (1998). Artificial Evolution of Visual
Control Systems for Robots.
* Dale, K. (1994). Evolving Neural Network Controllers for Task Defined
Robots. School of Cognitive
and Computing Sciences, University of Sussex.
* Floreano, D. and F. Mondada (1998). Active Perception, Navigation,
Homing, and Grasping: An
Autonomous Perspective.
* Garces?Perez, J., D. A. Schoenefeld, et al. (1996). Solving Facility
Layout Problems Using Genetic
Programming. Genetic Programming, First Annual Conference, MIT Press.
* Giuditta, A., M. V. Ambrosini, et al. (1995). "The Sequential
Hypothesis of the Function of Sleep."
Behavioural Brain Research 69(1-2): 157-66.
* Goldberg, D. E. (1994). "Genetic and Evolutionary Algorithms Come of
Age." Communications of the
ACM 37(3): 113-119.
* Goldish, A. (1996). Nosy Wall Following and Maze Navigation Through
Genetic Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Harris, C. and B. Buxton (1996). Evolving Edge Detectors with Genetic
Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Harvey, I., P. Husbands, et al. (1992). Issues in Evolutionary
Robotics, School of Cognitive and
Computing Sciences. University of Sussex.
* Nolfi, S. and D. Parisi (1997). "Learning to Adapt to Changing
Environments in Evolving Neural
Networks." Adaptive Behavior 5(1): 75-98.
* Nordin, P. and W. Banzhaf (1996). Programmatic Compression of Images
and Sound. Genetic
Programming, First Annual Conference, MIT Press.
* Poli, R. (1996). Genetic Programming for Image Analysis. Genetic
Programming, First Annual
Conference, MIT Press.
* Qureshi, A. (1996). Evolving Agents. Genetic Programming, First Annual
Conference, MIT Press.
a single, phylogenetically older sleep state. We hypothesize that the
physiological changes that
* Siegel, J. M., P. R. Manger, et al. (1996). "The Echidna Tachyglossus
Aculeatus Combines REM and
non-REM Aspects in a Single Sleep State: Implications for the Evolution
of Sleep." Journal of
Neuroscience 16(10): 3500-6.
* Takuya, I., I. Hitoshi, et al. (1996). Robustness of Robot Programs
Generated by Genetic
Programming. Genetic Programming, First Annual Conference, MIT Press.
to:
* Brave, S. (1996). The Evolution of Memory and Mental Models Using Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Chalmers, D. J. (1991). The Evolution of Learning: An Experiment in Genetic Connectionism. Proceedings of the 1990 Connectionist Models Summer School.
* Cliff, D., I. Harvey, et al. (1992). Incremantal Evolution of Neural Network Architectures for Adaptive Behaviour, School of Cognitive and Computing Sciences. University of Sussex.
* Cliff, D., I. Harvey, et al. (1998). Artificial Evolution of Visual Control Systems for Robots.
* Dale, K. (1994). Evolving Neural Network Controllers for Task Defined Robots. School of Cognitive and Computing Sciences, University of Sussex.
* Floreano, D. and F. Mondada (1998). Active Perception, Navigation, Homing, and Grasping: An Autonomous Perspective.
* Garces?Perez, J., D. A. Schoenefeld, et al. (1996). Solving Facility Layout Problems Using Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Giuditta, A., M. V. Ambrosini, et al. (1995). "The Sequential Hypothesis of the Function of Sleep." Behavioural Brain Research 69(1-2): 157-66.
* Goldberg, D. E. (1994). "Genetic and Evolutionary Algorithms Come of Age." Communications of the ACM 37(3): 113-119.
* Goldish, A. (1996). Nosy Wall Following and Maze Navigation Through Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Harris, C. and B. Buxton (1996). Evolving Edge Detectors with Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Harvey, I., P. Husbands, et al. (1992). Issues in Evolutionary Robotics, School of Cognitive and Computing Sciences. University of Sussex.
* Nolfi, S. and D. Parisi (1997). "Learning to Adapt to Changing Environments in Evolving Neural Networks." Adaptive Behavior 5(1): 75-98.
* Nordin, P. and W. Banzhaf (1996). Programmatic Compression of Images and Sound. Genetic Programming, First Annual Conference, MIT Press.
* Poli, R. (1996). Genetic Programming for Image Analysis. Genetic Programming, First Annual Conference, MIT Press.
* Qureshi, A. (1996). Evolving Agents. Genetic Programming, First Annual Conference, MIT Press.
* Siegel, J. M., P. R. Manger, et al. (1996). "The Echidna Tachyglossus Aculeatus Combines REM and non-REM Aspects in a Single Sleep State: Implications for the Evolution of Sleep." Journal of Neuroscience 16(10): 3500-6.
* Takuya, I., I. Hitoshi, et al. (1996). Robustness of Robot Programs Generated by Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Chalmers, D. J. (1991). The Evolution of Learning: An Experiment in Genetic Connectionism. Proceedings of the 1990 Connectionist Models Summer School.
* Cliff, D., I. Harvey, et al. (1992). Incremantal Evolution of Neural Network Architectures for Adaptive Behaviour, School of Cognitive and Computing Sciences. University of Sussex.
* Cliff, D., I. Harvey, et al. (1998). Artificial Evolution of Visual Control Systems for Robots.
* Dale, K. (1994). Evolving Neural Network Controllers for Task Defined Robots. School of Cognitive and Computing Sciences, University of Sussex.
* Floreano, D. and F. Mondada (1998). Active Perception, Navigation, Homing, and Grasping: An Autonomous Perspective.
* Garces?Perez, J., D. A. Schoenefeld, et al. (1996). Solving Facility Layout Problems Using Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Giuditta, A., M. V. Ambrosini, et al. (1995). "The Sequential Hypothesis of the Function of Sleep." Behavioural Brain Research 69(1-2): 157-66.
* Goldberg, D. E. (1994). "Genetic and Evolutionary Algorithms Come of Age." Communications of the ACM 37(3): 113-119.
* Goldish, A. (1996). Nosy Wall Following and Maze Navigation Through Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Harris, C. and B. Buxton (1996). Evolving Edge Detectors with Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
* Harvey, I., P. Husbands, et al. (1992). Issues in Evolutionary Robotics, School of Cognitive and Computing Sciences. University of Sussex.
* Nolfi, S. and D. Parisi (1997). "Learning to Adapt to Changing Environments in Evolving Neural Networks." Adaptive Behavior 5(1): 75-98.
* Nordin, P. and W. Banzhaf (1996). Programmatic Compression of Images and Sound. Genetic Programming, First Annual Conference, MIT Press.
* Poli, R. (1996). Genetic Programming for Image Analysis. Genetic Programming, First Annual Conference, MIT Press.
* Qureshi, A. (1996). Evolving Agents. Genetic Programming, First Annual Conference, MIT Press.
* Siegel, J. M., P. R. Manger, et al. (1996). "The Echidna Tachyglossus Aculeatus Combines REM and non-REM Aspects in a Single Sleep State: Implications for the Evolution of Sleep." Journal of Neuroscience 16(10): 3500-6.
* Takuya, I., I. Hitoshi, et al. (1996). Robustness of Robot Programs Generated by Genetic Programming. Genetic Programming, First Annual Conference, MIT Press.
Changed lines 1-83 from:
to:
References that Anthony has.
* Balakrishnan, K. and V. Honavar (1996). On Sensor Evolution in Robots. Genetic Programming, First Annual Conference, MIT Press.
* B?ck, T., U. Hammel, et al. (1997). "Evolutionary Computation: Comments On The History and Current State." IEEE Transactions on Evolutionary Computation 1(1):
3-17.
* Brave, S. (1996). The Evolution of Memory and Mental Models Using
Genetic Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Chalmers, D. J. (1991). The Evolution of Learning: An Experiment in
Genetic Connectionism.
Proceedings of the 1990 Connectionist Models Summer School.
* Cliff, D., I. Harvey, et al. (1992). Incremantal Evolution of Neural
Network Architectures for
Adaptive Behaviour, School of Cognitive and Computing Sciences.
University of Sussex.
* Cliff, D., I. Harvey, et al. (1998). Artificial Evolution of Visual
Control Systems for Robots.
* Dale, K. (1994). Evolving Neural Network Controllers for Task Defined
Robots. School of Cognitive
and Computing Sciences, University of Sussex.
* Floreano, D. and F. Mondada (1998). Active Perception, Navigation,
Homing, and Grasping: An
Autonomous Perspective.
* Garces?Perez, J., D. A. Schoenefeld, et al. (1996). Solving Facility
Layout Problems Using Genetic
Programming. Genetic Programming, First Annual Conference, MIT Press.
* Giuditta, A., M. V. Ambrosini, et al. (1995). "The Sequential
Hypothesis of the Function of Sleep."
Behavioural Brain Research 69(1-2): 157-66.
* Goldberg, D. E. (1994). "Genetic and Evolutionary Algorithms Come of
Age." Communications of the
ACM 37(3): 113-119.
* Goldish, A. (1996). Nosy Wall Following and Maze Navigation Through
Genetic Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Harris, C. and B. Buxton (1996). Evolving Edge Detectors with Genetic
Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Harvey, I., P. Husbands, et al. (1992). Issues in Evolutionary
Robotics, School of Cognitive and
Computing Sciences. University of Sussex.
* Nolfi, S. and D. Parisi (1997). "Learning to Adapt to Changing
Environments in Evolving Neural
Networks." Adaptive Behavior 5(1): 75-98.
* Nordin, P. and W. Banzhaf (1996). Programmatic Compression of Images
and Sound. Genetic
Programming, First Annual Conference, MIT Press.
* Poli, R. (1996). Genetic Programming for Image Analysis. Genetic
Programming, First Annual
Conference, MIT Press.
* Qureshi, A. (1996). Evolving Agents. Genetic Programming, First Annual
Conference, MIT Press.
a single, phylogenetically older sleep state. We hypothesize that the
physiological changes that
* Siegel, J. M., P. R. Manger, et al. (1996). "The Echidna Tachyglossus
Aculeatus Combines REM and
non-REM Aspects in a Single Sleep State: Implications for the Evolution
of Sleep." Journal of
Neuroscience 16(10): 3500-6.
* Takuya, I., I. Hitoshi, et al. (1996). Robustness of Robot Programs
Generated by Genetic
Programming. Genetic Programming, First Annual Conference, MIT Press.
* Wayner, P. (1991). "Genetic Algorithms." Byte: 361-366.
* Balakrishnan, K. and V. Honavar (1996). On Sensor Evolution in Robots. Genetic Programming, First Annual Conference, MIT Press.
* B?ck, T., U. Hammel, et al. (1997). "Evolutionary Computation: Comments On The History and Current State." IEEE Transactions on Evolutionary Computation 1(1):
3-17.
* Brave, S. (1996). The Evolution of Memory and Mental Models Using
Genetic Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Chalmers, D. J. (1991). The Evolution of Learning: An Experiment in
Genetic Connectionism.
Proceedings of the 1990 Connectionist Models Summer School.
* Cliff, D., I. Harvey, et al. (1992). Incremantal Evolution of Neural
Network Architectures for
Adaptive Behaviour, School of Cognitive and Computing Sciences.
University of Sussex.
* Cliff, D., I. Harvey, et al. (1998). Artificial Evolution of Visual
Control Systems for Robots.
* Dale, K. (1994). Evolving Neural Network Controllers for Task Defined
Robots. School of Cognitive
and Computing Sciences, University of Sussex.
* Floreano, D. and F. Mondada (1998). Active Perception, Navigation,
Homing, and Grasping: An
Autonomous Perspective.
* Garces?Perez, J., D. A. Schoenefeld, et al. (1996). Solving Facility
Layout Problems Using Genetic
Programming. Genetic Programming, First Annual Conference, MIT Press.
* Giuditta, A., M. V. Ambrosini, et al. (1995). "The Sequential
Hypothesis of the Function of Sleep."
Behavioural Brain Research 69(1-2): 157-66.
* Goldberg, D. E. (1994). "Genetic and Evolutionary Algorithms Come of
Age." Communications of the
ACM 37(3): 113-119.
* Goldish, A. (1996). Nosy Wall Following and Maze Navigation Through
Genetic Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Harris, C. and B. Buxton (1996). Evolving Edge Detectors with Genetic
Programming. Genetic
Programming, First Annual Conference, MIT Press.
* Harvey, I., P. Husbands, et al. (1992). Issues in Evolutionary
Robotics, School of Cognitive and
Computing Sciences. University of Sussex.
* Nolfi, S. and D. Parisi (1997). "Learning to Adapt to Changing
Environments in Evolving Neural
Networks." Adaptive Behavior 5(1): 75-98.
* Nordin, P. and W. Banzhaf (1996). Programmatic Compression of Images
and Sound. Genetic
Programming, First Annual Conference, MIT Press.
* Poli, R. (1996). Genetic Programming for Image Analysis. Genetic
Programming, First Annual
Conference, MIT Press.
* Qureshi, A. (1996). Evolving Agents. Genetic Programming, First Annual
Conference, MIT Press.
a single, phylogenetically older sleep state. We hypothesize that the
physiological changes that
* Siegel, J. M., P. R. Manger, et al. (1996). "The Echidna Tachyglossus
Aculeatus Combines REM and
non-REM Aspects in a Single Sleep State: Implications for the Evolution
of Sleep." Journal of
Neuroscience 16(10): 3500-6.
* Takuya, I., I. Hitoshi, et al. (1996). Robustness of Robot Programs
Generated by Genetic
Programming. Genetic Programming, First Annual Conference, MIT Press.
* Wayner, P. (1991). "Genetic Algorithms." Byte: 361-366.
Page last modified on January 12, 2005, at 02:50 AM