3 citations · 5 across the 6 of their papers we have counts for
7 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…
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…
Dependence in Propositional Logic: Formula-Formula Dependence and Formula Forgetting -- Application to Belief Update and Conservative Extension
Liangda Fang, Hai Wan, Xianqiao Liu +2
Dependence is an important concept for many tasks in artificial intelligence. A task can be executed more efficiently by discarding something independent from the task. In this pap…
A General Multi-agent Epistemic Planner Based on Higher-order Belief Change
Xiao Huang, Biqing Fang, Hai Wan +1
In recent years, multi-agent epistemic planning has received attention from both dynamic logic and planning communities. Existing implementations of multi-agent epistemic planning…