Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Chunking in Shogi: New Findings

Authors: Takeshi Ito; Hitoshi Matsubara; Reijer Grimbergen;

Chunking in Shogi: New Findings

Abstract

In the past, there have been numerous studies into the cognitive processes involved in human problem solving. From the start, games and game theory have played an important role in the study of human problem solving behavior. In Chess, several cognitive experiments have been performed and those experiments have shown that expert chess players can memorize positions very quickly and accurately. Chase and Simon introduced the concept of chunking to explain why expert chess players perform so well in memory tasks. Chunking is the process of dividing a chess position into smaller parts that have meaning. We performed similar experiments in Shogi with a set of next-move problem positions, collecting verbal protocol data and eye-movement data. Even though experiments in Chess indicated that expert chess players searched as wide and deep as non-expert players, our experiments show that expert Shogi players search more moves, search deeper and search faster than non-expert players. Our experiments also show that expert Shogi players cannot only memorize the patterns of the positions but also recognize move sequences before and after the position. The results suggest that other than the perceptual spatial chunks introduced in chess research, there are also chunks of meaningful move sequences. We call such chunks “temporal chunk”. Our research indicates that Shogi players become stronger by acquiring these temporal chunks.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!