Proceedings:
No. 1: Thirty-First AAAI Conference On Artificial Intelligence
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 31
Track:
Student Abstract Track
Downloads:
Abstract:
Recent enhancements to greedy best-first search (GBFS) improve performance by occasionally adopting a non-greedy node expansion policy, resulting in more exploratory behavior. However, previous exploratory mechanisms do not address exploration within the space sharing the same heuristic estimate (plateau) and the search bias in a breadth direction. In this abstract, we briefly describe two modes of exploration (diversification), which work inter-(across) and intra-(within) plateau, and also introduce IP-diversification, a method combining Minimum Spanning Tree and randomization, which addresses ÒbreadthÓ-bias instead of the ÒdepthÓ-bias addressed by the existing methods.
DOI:
10.1609/aaai.v31i1.11093
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 31