leeo
Regular
I here wish to advocate a TuRBo-like approach, and compare it with the Beyer-Hardwick (BH) method. It seems interest in TuRBo has fallen off in favor of Beyer-Hardwick (BH) methods. Both methods solve two elements at a time, usually memorized as a letter pair. However, in BH, about six to eight optimal edge and corner patterns are mastered, and formed on the fly to match a letter pair. In TuRBo, a core set of about twenty algorithms is acquired, and brought to match any letter pair with setup moves.
Many approaches to acquiring BH involve studying every possible letter pair. There are 1009 corner letter pairs and 1760 edge letter pairs -- but if you pick a fixed buffer the number drops to 378 corner letter pairs and 440 edges letter pairs. Acquiring 818 algorithms is achievable, since most follow common patterns.
Still I find the TuRBo-like approach more achievable, or easier to acquire. Once I pick a target algorithm, I can spend much more time to optimize it or learn a fingering for it. Daily practice brings it to muscle memory within a week. The problem of mis-identifying reversed algorithms can be alleviated somewhat by learning slightly different reversed-direction algorithms, say a face-turn away.
My original modification of TuRBo had seven corner algorithms that could be contorted to cover all 378 corner letter pairs -- however I found it easier to learn additional algorithms than to master all of the contortion types. I have recently settled on 20 corner algorithms and two very simple setup types to cover every letter pair. The situation for the edges is similar.
I am working on a computer program that generates the setup moves for a set of letter pairs for any desired buffer, showing how it covers every letter-pair target off that buffer. Internally, all 2769 possible edge and corner letter pairs are generated by following the BH patterns. A letter pair set is entered, and the setup moves are calculated. A score is generated comparing the extra moves for every letter pair compared to the optimal BH. I had this ability for a few years, but currently I am re-engineering the program to support any letter system, and any reading orientation.
With the ability to generate such a list, a core set of algorithms can be selected and practiced with "under the table" solves.
Many approaches to acquiring BH involve studying every possible letter pair. There are 1009 corner letter pairs and 1760 edge letter pairs -- but if you pick a fixed buffer the number drops to 378 corner letter pairs and 440 edges letter pairs. Acquiring 818 algorithms is achievable, since most follow common patterns.
Still I find the TuRBo-like approach more achievable, or easier to acquire. Once I pick a target algorithm, I can spend much more time to optimize it or learn a fingering for it. Daily practice brings it to muscle memory within a week. The problem of mis-identifying reversed algorithms can be alleviated somewhat by learning slightly different reversed-direction algorithms, say a face-turn away.
My original modification of TuRBo had seven corner algorithms that could be contorted to cover all 378 corner letter pairs -- however I found it easier to learn additional algorithms than to master all of the contortion types. I have recently settled on 20 corner algorithms and two very simple setup types to cover every letter pair. The situation for the edges is similar.
I am working on a computer program that generates the setup moves for a set of letter pairs for any desired buffer, showing how it covers every letter-pair target off that buffer. Internally, all 2769 possible edge and corner letter pairs are generated by following the BH patterns. A letter pair set is entered, and the setup moves are calculated. A score is generated comparing the extra moves for every letter pair compared to the optimal BH. I had this ability for a few years, but currently I am re-engineering the program to support any letter system, and any reading orientation.
With the ability to generate such a list, a core set of algorithms can be selected and practiced with "under the table" solves.
