10 citations · 18 across the 11 of their papers we have counts for
5 papers · 1 filter
Refining HTN Methods via Task Insertion with Preferences
Zhanhao Xiao, Hai Wan, Hankui Hankz Zhuo +3
Hierarchical Task Network (HTN) planning is showing its power in real-world planning. Although domain experts have partial hierarchical domain knowledge, it is time-consuming to sp…
An Incremental Evaluation Mechanism for the Critical Node Problem
Biqing Fang, Hai Wan, Shaowei Cai +1
The Critical Node Problem (CNP) is to identify a subset of nodes in a graph whose removal maximally degrades pairwise connectivity. The CNP is an important variant of the Critical…
Representation Learning for Classical Planning from Partially Observed Traces
Zhanhao Xiao, Hai Wan, Hankui Hankz Zhuo +2
Specifying a complete domain model is time-consuming, which has been a bottleneck of AI planning technique application in many real-world scenarios. Most classical domain-model lea…
CoAPI: An Efficient Two-Phase Algorithm Using Core-Guided Over-Approximate Cover for Prime Compilation of Non-Clausal Formulae
Weilin Luo, Hai Wan, Hongzhen Zhong +1
Prime compilation, i.e., the generation of all prime implicates or implicants (primes for short) of formulae, is a prominent fundamental issue for AI. Recently, the prime compilati…
Combining Reinforcement Learning and Configuration Checking for Maximum k-plex Problem
Peilin Chen, Hai Wan, Shaowei Cai +2
The Maximum k-plex Problem is an important combinatorial optimization problem with increasingly wide applications. Due to its exponential time complexity, many heuristic methods ha…