Akira Imada - researchr alias

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Viewing Publication 1 - 22 from 22

2014

What Is Machine Intelligence? A Case Study: Stock Market Forecasting AgentsAkira Imada. acs2 2015: 3-10 [doi]

2013

Artificial Intelligence Evolved from Random Behaviour: Departure from the State of the ArtWieslaw Pietruszkiewicz, Akira Imada. In Xin-She Yang, editor, Artificial Intelligence, Evolutionary Computing and Metaheuristics - In the Footsteps of Alan Turing. Volume 427 of Studies in Computational Intelligence, pages 19-41, Springer, 2013. [doi]

2011

Is Artificial Neural Network Intelligent?Akira Imada. ijcomputing, 10(1):66-76, 2011. [doi]

2007

Finding a Needle in a Haystack: From Baldwin Effect to Quantum ComputationAkira Imada. cisim 2007: 20-25 [doi]

When a Family of Iris Flower is Normal, Then are Others Abnormal?Akira Imada. In Jerzy Pejas, Khalid Saeed 0001, editors, Advances in Information Processing and Protection. pages 205-214, Springer, 2007. [doi]

2006

Can a Negative Selection Detect an Extremely few Non-self among Enormous Amount of Self Cells?Akira Imada. In Khalid Saeed 0001, Jerzy Pejas, Romuald Mosdorf, editors, Biometrics, Computer Security Systems and Artificial Intelligence Applications. pages 217-226, Springer, 2006. [doi]

How Many Parachutists will be Necessary to Find a needle in a pastoral - who is a Lucky One?Akira Imada. ijcomputing, 5(3):126-134, 2006. [doi]

2005

Can a Fuzzy Rule Extraction Find an Extremely Tiny non-Self Region?Akira Imada. anns 2005: 35-41

Can a Fuzzy Rule Look for a Needle in a Haystack?Akira Imada. tainn 2006: 133-140 [doi]

A Tiny Flat-island in a Huge Lake - How can we search for it if completely flatland elsewhere?Akira Imada. In Khalid Saeed 0001, Jerzy Pejas, editors, Information Processing and Security Systems. pages 353-364, Springer, 2005. [doi]

2004

How a peak can be Searched for in an Almost everywhere Flatland of Altitude Zero? - Tiny flat Island in Huge LakeAkira Imada. ijcomputing, 3(1):32-37, 2004. [doi]

1999

Downhill walk from the top of a hill by evolutionary programmingAkira Imada. cec 1999: 1414-1418 [doi]

What Does a Peak in the Landscape of a Hopfield Associative Memory Look Like ?Akira Imada. iwann 1999: 357-366

1998

What does the Landscape of a Hopfield Associative Memory Look Like?Akira Imada, Keijiro Araki. eps 1998: 647-656

Can a Niching Method Locate Multiple Attractors Embedded in the Hopfield Network?Akira Imada, Keijiro Araki. seal 1999: 325-332 [doi]

How Real-valued Random Synapses Evolve Toward Symmetry with Diploid Chromosomes?Akira Imada, Keijiro Araki. nc 1998: 164-169

1997

The Baldwin Effect on the Evolution of Associative MemoryAkira Imada, Keijiro Araki. icannga 1998: 354-358 [doi]

Searching Real-Valued Synaptic Weights of Hopfield s Associative Memory Using Evolutionary ProgrammingAkira Imada, Keijiro Araki. eps 1997: 13-22

Random Perturbations to Hebbian Synapses of Associative Memory Using a Genetic AlgorithmAkira Imada, Keijiro Araki. iwann 1997: 398-407

Evolution of Hopfield Model of Associative Memory by the Breeder Genetic AlgorithmAkira Imada, Keijiro Araki. icga 1997: 784-791

1996

Lamarckian Evolution of Associative MemoryAkira Imada, Keijiro Araki. icec 1996: 676-680

1995

Genetic Algorithm Enlarges the Capacity of Associative MemoryAkira Imada, Keijiro Araki. icga 1995: 413-420

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