Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Yufei Wu 0008

dblp:241/7663 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0002-1792-2306ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Multi-agent systems · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Environmental and earth informatics · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › game theory
game-theoretic modeling
0.912025
Improving Community-Participated Patrol for Anti-Poaching · AAAI 2025
Environmental and earth informatics
environmental informatics
0.912025
Improving Community-Participated Patrol for Anti-Poaching · AAAI 2025

Methods — techniques the papers use, named apart from their topics

waterfilling algorithm · 1.7binary search · 1.7mixed-integer linear programming · 0.9mixed integer linear programming · 0.9
YearPublicationVenuePosition
2025 Improving Community-Participated Patrol for Anti-Poaching
abstract
Community engagement plays a critical role in anti-poaching efforts, yet existing mathematical models aimed at enhancing this engagement often overlook direct participation by community members as alternative patrollers. Unlike professional rangers, community members typically lack flexibility and experience, resulting in new challenges in optimizing patrol resource allocation. To address this gap, we propose a novel game-theoretic model for community-participated patrol, where a conservation agency strategically deploys both professional rangers and community members to safeguard wildlife against a best-responding poacher. In addition to a mixed-integer linear program formulation, we introduce a Two-Dimensional Binary Search algorithm and a novel Hybrid Waterfilling algorithm to efficiently solve the game in polynomial time. Through extensive experiments and a detailed case study focused on a protected tiger habitat in Northeast China, we demonstrate the effectiveness of our algorithms and the practical applicability of our model.
Yufei Wu 0008, Yixuan Even Xu, Shibing Zhu, Fei Fang 0001
AAAI1