Search Results for author: Azlan Iqbal

Found 9 papers, 0 papers with code

A Novel Machine Learning Method for Preference Identification

no code implementations22 Oct 2020 Azlan Iqbal

Human preference or taste within any domain is usually a difficult thing to identify or predict with high probability.

BIG-bench Machine Learning

An Algorithm for Automatically Updating a Forsyth-Edwards Notation String Without an Array Board Representation

no code implementations2 Sep 2020 Azlan Iqbal

We present an algorithm that correctly updates the Forsyth-Edwards Notation (FEN) chessboard character string after any move is made without the need for an intermediary array representation of the board.

Board Games

The Effects of Quantum Randomness on a System Exhibiting Computational Creativity

no code implementations22 Aug 2020 Azlan Iqbal

We present experimental results on the effects of using quantum or 'truly' random numbers, as opposed to pseudorandom numbers, in a system that exhibits computational creativity (given its ability to compose original chess problems).

Estimating Total Search Space Size for Specific Piece Sets in Chess

no code implementations27 Feb 2018 Azlan Iqbal

However, it is useful to be able to estimate what the search space size for particular piece combinations is to begin with.

A Computer Composes A Fabled Problem: Four Knights vs. Queen

no code implementations4 Sep 2017 Azlan Iqbal

We explain how the prototype automatic chess problem composer, Chesthetica, successfully composed a rare and interesting chess problem using the new Digital Synaptic Neural Substrate (DSNS) computational creativity approach.

A Chain-Detection Algorithm for Two-Dimensional Grids

no code implementations12 Oct 2016 Paul Bonham, Azlan Iqbal

Presently, no foolproof method of detecting such chains in any given chess position is known and existing graph theory, to our knowledge, is unable to fully address this problem either.

Position valid +1

The Digital Synaptic Neural Substrate: Size and Quality Matters

no code implementations20 Sep 2016 Azlan Iqbal

We investigate the 'Digital Synaptic Neural Substrate' (DSNS) computational creativity approach further with respect to the size and quality of images that can be used to seed the process.

The Digital Synaptic Neural Substrate: A New Approach to Computational Creativity

no code implementations25 Jul 2015 Azlan Iqbal, Matej Guid, Simon Colton, Jana Krivec, Shazril Azman, Boshra Haghighi

It uses selected attributes from objects in various domains (e. g. chess problems, classical music, renowned artworks) and recombines them in such a way as to generate new attributes that can then, in principle, be used to create novel objects of creative value to humans relating to any one of the source domains.

Open-Ended Question Answering

How Relevant Are Chess Composition Conventions?

no code implementations12 Sep 2013 Azlan Iqbal

Second, human judges either do not look at the same conventions related to aesthetics in the model used or emphasize others that have less to do with beauty as perceived by the majority of players, even though they may mistakenly consider their judgements beautiful in the traditional, non-esoteric sense.

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