activity
20122026
most citedSolving Multistage Influence Diagrams using Branch-and-Bound Search

10 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Agentopia: Long-Term Life Simulation and Learning in Agent Societies

Xintao Wang, Sirui Zheng, Hongqiu Wu +10

Humans learn from social life. Simulating this process with LLM-powered agents represents a promising research direction, raising a natural question: whether LLMs can learn from su…

cs.AI2017

Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Network

Johan Bjorck, Yiwei Bai, Xiaojian Wu +3

Cascades represent rapid changes in networks. A cascading phenomenon of ecological and economic impact is the spread of invasive species in geographic landscapes. The most promisin…

cs.AI2017★ 1 cited

XOR-Sampling for Network Design with Correlated Stochastic Events

Xiaojian Wu, Yexiang Xue, Bart Selman +1

Many network optimization problems can be formulated as stochastic network design problems in which edges are present or absent stochastically. Furthermore, protective actions can…

cs.AI2016★ 4 cited

Robust Optimization for Tree-Structured Stochastic Network Design

Xiaojian Wu, Akshat Kumar, Daniel Sheldon +1

Stochastic network design is a general framework for optimizing network connectivity. It has several applications in computational sustainability including spatial conservation pla…

cs.AI2012★ 10 cited

Solving Multistage Influence Diagrams using Branch-and-Bound Search

Changhe Yuan, Xiaojian Wu, Eric A. Hansen

A branch-and-bound approach to solving influ- ence diagrams has been previously proposed in the literature, but appears to have never been implemented and evaluated - apparently du…