Chess Imagination and Perceptual Understanding - Preprint (2013) (original) (raw)
Related papers
Perception in chess and beyond: Commentary on Linhares and Freitas (2010)
New Ideas in Psychology, 2011
Linhares and Freitas (2010; LF) argue that experts use analogical or semantic similarity, similarities that are not available from direct surface representations. LF make their case using a critique of Chase and Simon (1973b) and the presentation of a few chess positions and examples from other domains. Their conclusion is that models such as CHREST (Gobet et al., 2001) and theories such as the chunking theory (Chase & Simon, 1973b) and the template theory (Gobet & Simon, 1996) are inadequate for dealing with these issues. They propose an alternative paradigm, which they call "experience recognition." Although we find this issue an interesting one, the separation between pattern recognition and problem solving is a lot more complex than LF portray. We instead suggest that a "revolution" in our to date successful modelling is not necessary. Especially in the chess domain, LF's examples do not make the point they claim. Furthermore, their criticisms of CS are incorrect, and they have failed to mention a large number of experimental results that have supported the hypothesis of location-specific encodings. Although we agree that experts use semantic information and similarities, these ideas already possess analogues in CHREST, which can form the basis of further evolution of the theory.
Chess players' thinking revisited
1998
The main result of De Groot's ([1946] 1978) classical study of chessplayers' thinking was that players of various levels of skill do not differ in the macrostructure of their thought process (in particular with respect to the depth of search and to the number of nodes investigated). Recently, Holding (1985, 1992) challenged these results and proposed that there are skill differences in the way players explore the problem space. The present study replicates De Groot's (1978) problem solving experiment. Results show that Masters differ from weak players in more ways than found in the original study. Some of the differences support search models of chess thinking, and others pattern recognition models. The theoretical discussion suggests that the usual distinction between search and pattern recognition models of chess thinking is unwarranted, and proposes a way of reconciling the two approaches.
An Active Symbols Theory of Chess Intuition
The well-known game of chess has traditionally been modeled in artificial intelligence studies by search engines with advanced pruning techniques. The models were thus centered on an inference engine manipulating passive symbols in the form of tokens. It is beyond doubt, however, that human players do not carry out such processes. Instead, chess masters instead carry out perceptual processes, carefully categorizing the chunks perceived in a position and gradually building complex dynamic structures to represent the subtle pressures embedded in the positions. In this paper we will consider two hypotheses concerning the underlying subcognitive processes and architecture. In the first hypothesis, a multiple-leveled chess representational structure is presented, which includes distance graphs (with varying levels of quality) between pieces, piece mobilities, and abstract roles. These representational schemes seem to account for numerous characteristics of human player's psychology. The second hypothesis concerns the extension of the architecture proposed in the Copycat project as central for modeling the emergent intuitive perception of a chess position. We provide a synthesis on how the postulated architecture models chess intuition as an emergent mixture of simultaneous distance estimations, chunk perceptions, abstract role awareness, and intention activations. This is an alternative model to the traditional AI approaches, focusing on the philosophy of active symbols.
Intuitions without concepts lose the game: mindedness in the art of chess
To gain insight into human nature philosophers often discuss the inferior performance that results from deficits such as blindsight or amnesia. Less often do they look at superior abilities. A notable exception is Herbert Dreyfus who has developed a theory of expertise according to which expert action generally proceeds automatically and unreflectively. We address one of Dreyfus's primary examples of expertise: chess. At first glance, chess would seem an obvious counterexample to Dreyfus's view since, clearly, chess experts are engaged in deep strategic thought. However, Dreyfus's argument is subtle. He accepts that analysis and deliberation play a role in chess, yet he thinks that all such thought is predicated on intuitive, arational expert perception, and action. We argue that even the so-called "intuitive" aspect of chess is rational through and through.
Chess Capyblanca Linhares and Freitas 2010 New Ideas in Psychology
Pattern recognition lies at the heart of the cognitive science endeavor. In this paper, we provide some criticism of this notion, using studies of chess as an example. The game of chess is, as significant evidence shows, a game of abstractions: pressures; force; open files and ranks; time; tightness of defense; old strategies rapidly adapted to new situations. These ideas do not arise on current computational models, which apply brute force by rote-memorization. In this paper we assess the computational models of CHREST and CHUMP, and argue that chess chunks must contain semantic information. This argument leads to a new and contrasting claim, as we propose that key conclusions of Chase and Simon's (1973) influential study stemmed from a non-sequitur. In the concluding section, we propose a shift in philosophy, from ''pattern recognition'' to a framework of ''experience recognition''.
Chess Metaphors: Artificial Intelligence and the Human Mind
The European Legacy, 2015
... Contents Foreword by Jorge Wagensberg ix Preface xi 1 The Human Brain: Metaphor Maker 1 2 The Human Mind: Metaphor of the World 29 3 Artiļ¬cial Intelligence: Silicon Metaphors 61 4 The Complete Metaphor: Chess and Problem Solving 85 5 Chess Metaphors: Searches ...
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Chess and content-oriented psychology of thinking
2001
In this paper a number of principles for content-oriented cognitive psychology will be presented in the context of research into chess players' information processing. It will be argued that modern theoretical concepts of attention, imagery and memory are based on underlying concepts of capacity and format and that these concepts are not sufficiently powerful to express all phenomena associated with mental contents. Instead, one must develop a genuinely content-oriented theoretical language to discuss, for example, contents and their integration into thinking. The main problem is how to explain the contents of representations. Why do representations have precisely the contents that they have. Here the main attention will be focussed on the question how can one explain the selection of content elements in representations. To formulate the basic concepts of content- oriented thought research several issues must be discussed. Firstly, it will be shown that traditional attention an...
Computational Modelling of Mental Imagery in Chess: A Sensitivity Analysis
2008
An important aim of cognitive science is to build computational models that account for a large number of phenomena but have few free parameters, and to obtain more veridical values for the models' parameters by successive approximations. A good example of this approach is the CHREST model (Gobet & Simon, 2000), which has simulated numerous phenomena on chess expertise and in other domains. In this paper, we are interested in the parameter the model uses for shifting chess pieces in its mind's eye (125 ms per piece), a parameter that had been estimated based on relatively sparse experimental evidence. Recently, Waters and Gobet (2008) tested the validity of this parameter in a memory experiment that required players to recall briefly presented positions in which the pieces were placed on the intersections between squares. Position types ranged from game positions to positions where both the piece distribution and location were randomised. CHREST, which assumed that pieces must be centred back to the middle of the squares in the mind's eye before chunks can be recognized, simulated the data fairly well using the default parameter for shifting pieces. The sensitivity analysis presented in the current paper shows that the fit was nearly optimal for all groups of players except the grandmaster group for which, counterintuitively, a slower shifting time gave a better fit. The implications for theory development are discussed.