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Danny Kopec

dblp:89/674 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 1999
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1Human-computer interaction and ubiquitous computing · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 67% Knowledge representation and reasoning · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › game playing
chess		 0.011990
A taxonomy of concepts for evaluating chess strength · SC 1990
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
game playing		 0.011990
A taxonomy of concepts for evaluating chess strength · SC 1990

Methods — techniques the papers use, named apart from their topics

taxonomy construction · 0.0
YearPublicationVenuePosition
1999 How should data structures and algorithms be taught
abstract
Data Structures and Algorithms is clearly a very important topic and course in the Computer Science curriculum. It has been taught at several levels by a number of approaches. Should the approach be mathematical, theoretical and abstract or very concrete and "hands on"? Whichever method is used, the ultimate goal is the same: enhancing student comprehension. The panelists discuss three distinct and well-defined approaches.
Danny Kopec, Richard T. Close, James R. Aman
 ITiCSE1
1990 A taxonomy of concepts for evaluating chess strength
abstract
The authors present a taxonomy of positions in chess that require special knowledge. The taxonomy drives the selection of positions, not vice-versa. The authors present a set of annotated example problems from two specific categories that require understanding of critical concepts to achieve the maximum result.>
Hans J. Berliner, Danny Kopec, Ed Northam
 SC2
1978 Pattern-Based Representation of Chess End-Game Knowledge
abstract
I. Bratko, D. Kopec, D. Michie; Pattern-Based Representation of Chess End-Game Knowledge, The Computer Journal, Volume 21, Issue 2, 1 May 1978, Pages 149–1
Ivan Bratko, Danny Kopec, Donald Michie
 Comput. J.2