Abstract
This paper presents a contribution to the ongoing debate about the impact of research in computer chess on artificial intelligence (AI), by critically examining the view ‘computer chess was good for AI’, which we believe is common to the majority of the scientific community involved. Our critique weakens the rationale behind the objection that the currently dominating hardware-intensive, brute-force-based engineering approach is responsible for the current situation. We show that, e.g., in natural-language processing, there is much similarity in terms of the sophistication of methods, the role of hardware, and the contrast between theory and practice. We argue that the role of computer chess in artificial intelligence can be strengthened by putting new efforts in generalizing extant methods and transferring their key ideas to other areas within AI.
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