Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Conspiracy numbers for min-max search
Artificial Intelligence
The History Heuristic and Alpha-Beta Search Enhancements in Practice
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence
Singular extensions: adding selectivity to brute-force searching
Artificial Intelligence - Special issue on computer chess
BIDA: an improved perimeter search algorithm
Artificial Intelligence
Performance of linear-space search algorithms
Artificial Intelligence
Enhanced Iterative-Deepening Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pushing the limits: new developments in single-agent search
Pushing the limits: new developments in single-agent search
Human Problem Solving
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
AFIPS '67 (Fall) Proceedings of the November 14-16, 1967, fall joint computer conference
Complete solution of the eight-puzzle and the benefit of node ordering in IDA
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Domain-dependent single-agent search enhancements
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
How to use limited memory in heuristic search
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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The seminal works of Nilsson and Pearl in the 1970's and early 1980's provide a formal basis for splitting the field of heuristic search into two subfields: single- and two-agent search. The subfields are studied in relative isolation from each other; each having its own distinct character. Despite the separation, a close inspection of the research shows that the two areas have actually been converging. This paper argues that the single/two-agent distinction is not the essence of heuristic search anymore. The state space is characterized by a number of key properties that are defined by the application; single- versus two-agent is just one of many. Both subfields have developed many search enhancements; they are shown to be surprisingly similar and general. Given their importance for creating high performance search applications, it is these enhancements that form the essence of our field. Focusing on their generality emphasizes the opportunity for reuse of the enhancements, allows the field of heuristic search to be redefined as a single unified field, and points the way towards a modern theory of search based on the taxonomy proposed here.