{"id":1078,"date":"2012-02-15T14:11:27","date_gmt":"2012-02-15T20:11:27","guid":{"rendered":"http:\/\/theinvisiblegorilla.com\/blog\/?p=1078"},"modified":"2012-02-15T14:20:09","modified_gmt":"2012-02-15T20:20:09","slug":"how-experts-recall-chess-positions","status":"publish","type":"post","link":"http:\/\/theinvisiblegorilla.com\/blog\/2012\/02\/15\/how-experts-recall-chess-positions\/","title":{"rendered":"How experts recall chess positions"},"content":{"rendered":"

In 2011, a computer (Watson<\/a>) outplayed two human Jeopardy champions.\u00a0 In 1997, chess computer Deep Blue<\/a> defeated chess champion Garry Kasparov<\/a>. In both cases, the computer \u201csolved\u201d the game\u2014found the right questions or good moves\u2014differently than humans do.\u00a0 Defeating humans in these domains took years of research and programming by teams of engineers, but only with huge advantages in speed, efficiency, memory, and precision could computers compete with much more limited humans.<\/p>\n

What allows human experts to match wits with custom-designed computers equipped with tremendous processing power?\u00a0 Chess players have a limited ability to evaluate all of the possible moves, the responses to those moves, the responses to the responses, etc. Even if they could evaluate all of the possible alternatives several moves deep, they still would need to remember which moves they had evaluated, which ones led to the best outcomes, and so on.\u00a0 Computers expend no effort remembering possibilities that they had already rejected or revisiting options that proved unfruitful.<\/p>\n

This question, how do chess experts evaluate positions to find the best move, has been studied for decades, dating back to the groundbreaking work of Adriaan de Groot<\/a> and later to work by William Chase and Herbert Simon<\/a>.\u00a0 de Groot interviewed several chess players as they evaluated positions, and he argued that experts and weaker players tended to \u201clook\u201d about the same number of moves ahead and to evaluate similar numbers of moves with roughly similar speed.\u00a0 The relatively small differences between experts and novices suggested that their advantages came not from brute force calculation ability but from something else: knowledge.\u00a0 According to De Groot, the core of chess expertise is the ability to recognize huge number of chess positions (or parts of positions) and to derive moves from them.\u00a0 In short, their greater efficiency came not from evaluating more outcomes, but from considering only the better options.\u00a0[Note: Some of the details of de Groot\u2019s claims, which he made before the appropriate statistical tests were in widespread use, did not hold up to later scrutiny\u2014experts do consider somewhat more options, look a bit deeper, and process positions faster than less expert players (Holding, 1992). But de Groot was right about the limited nature of expert search and the importance of knowledge and pattern recognition in expert performance.]<\/em><\/p>\n

In de Groot\u2019s most famous demonstration, he showed several players images of chess positions for a few seconds and asked the players to reconstruct the positions from memory.\u00a0 The experts made relatively few mistakes even though they had seen the position only briefly.\u00a0 Years later, Chase and Simon replicated de Groot\u2019s finding with another expert (a master-level player) as well as an amateur and a novice.\u00a0 They also added a critical control: The players viewed both real chess positions and scrambled chess positions (that included pieces in implausible and even impossible locations). The expert excelled with the real positions, but performed no better than the amateur and novice for the scrambled positions (later studies showed that experts can perform slightly better than novices for random positions too if given enough time; Gobet & Simon, 1996).\u00a0 The expert advantage apparently comes from familiarity with real chess positions, something that allows more efficient encoding or retrieval of the positions.<\/p>\n

Chase and Simon recorded their expert performing the chess reconstruction task, and found that he placed the pieces on the board in spatially contiguous chunks, with pauses of a couple seconds after he reproduced each chunk.\u00a0 This finding has become part of the canon of cognitive psychology: People can increase their working memory capacity by grouping together otherwise discrete pieces of items to form a larger unit in memory.\u00a0 In that way, we can encode more information into the same limited number of memory slots.<\/p>\n

They In 1998, Chris Chabris and I invited two-time US Champion and International Grandmaster Patrick Wolff (a friend of Chris\u2019s) to the lab and asked him to do the chess position reconstruction task. Wolff viewed each position (on a printed index card) for five seconds and then immediately reconstructed it on a chess board.\u00a0 After he was satisfied with his work, we gave him the next card.\u00a0 After he finished five real positions and five scrambled positions, we asked him to describe how he did the task.<\/p>\n

The video below shows his performance and his explanations (Chris is the one handing him the cards and holding the stopwatch\u2014I was behind the camera). Like other experts who have been tested, Wolff rarely made mistakes in reconstructing positions, and when he did, the errors were trivial\u2014they did not alter the fundamental meaning or structure of the position.\u00a0Watch for the interesting comments at the end when Wolff describes why he was focused on some aspects of a position but not others.<\/p>\n

<\/embed><\/object><\/p>\n

HT to Chris Chabris for comments on a draft of this post<\/span><\/p>\n

Comments<\/strong>: Please make your comments on the Google+ notice of this post<\/a>. That will permit more interaction:<\/p>\n

Sources cited<\/strong>:<\/p>\n

For an extended discussion of chess expertise and the nature of expert memory, see Christopher Chabris\u2019s dissertation:\u00a0 Chabris, C. F. (1999).\u00a0 Cognitive and neuropsychological mechanisms of expertise: Studies with chess masters.\u00a0 Doctoral Dissertation, Harvard University. http:\/\/en.scientificcommons.org\/43254650<\/p>\n

Chase, W. G., & Simon, H. A. (1973).\u00a0 Perception in chess.\u00a0 Cognitive Psychology<\/em>, 4<\/em>, 55-81.<\/p>\n

de Groot, A.D. (1946). Het denken van de schaker.<\/em> [The thought of the chess player.] Amsterdam: North-Holland. (Updated translation published as Thought and choice in chess<\/em>, Mouton, The Hague, 1965; corrected second edition published in 1978.)<\/p>\n

Holding, D.H. (1992). Theories of chess skill. Psychological Research<\/em>, 54(1)<\/em>, 10\u201316.<\/p>\n

Gobet, F., & Simon, H.A. (1996a). Recall of rapidly presented random chess positions is a function of skill. Psychonomic Bulletin & Review, 3(2),<\/em> 159\u2013163.<\/p>\n","protected":false},"excerpt":{"rendered":"

In 2011, a computer (Watson) outplayed two human Jeopardy champions. In 1997, chess computer Deep Blue defeated chess champion Garry Kasparov. In both cases, the computer \u201csolved\u201d the game\u2014found the right questions or good moves\u2014differently than humans do. Defeating humans in these domains took years of research and programming by teams of engineers, but only with huge advantages in speed, efficiency, memory, and precision could computers compete with much more limited humans. What allows human experts to match wits with custom-designed computers equipped with tremendous processing power? […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17,35],"tags":[],"class_list":["post-1078","post","type-post","status-publish","format-standard","hentry","category-examples","category-memory"],"_links":{"self":[{"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/posts\/1078","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/comments?post=1078"}],"version-history":[{"count":9,"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/posts\/1078\/revisions"}],"predecessor-version":[{"id":1086,"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/posts\/1078\/revisions\/1086"}],"wp:attachment":[{"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/media?parent=1078"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/categories?post=1078"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/theinvisiblegorilla.com\/blog\/wp-json\/wp\/v2\/tags?post=1078"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}