T
Tad Hogg
Researcher at Xerox
Publications - 106
Citations - 5051
Tad Hogg is an academic researcher from Xerox. The author has contributed to research in topics: Constraint satisfaction problem & Incremental heuristic search. The author has an hindex of 32, co-authored 101 publications receiving 4878 citations. Previous affiliations of Tad Hogg include PARC.
Papers
More filters
Journal ArticleDOI
Spawn: a distributed computational economy
TL;DR: Using concurrent Monte Carlo simulations as prototypical applications, the authors explore issues of fairness in resource distribution, currency as a form of priority, price equilibria, the dynamics of transients, and scaling to large systems.
Journal ArticleDOI
An Economics Approach to Hard Computational Problems
TL;DR: This method, based on notions of risk in economics, offers a computational portfolio design procedure that can be used for a wide range of problems, including the combinatorics of DNA sequencing and the completion of tasks in environments with resource contention, such as the World Wide Web.
Journal ArticleDOI
The DARPA Twitter Bot Challenge
V. S. Subrahmanian,Amos Azaria,Skylar Durst,Vadim Kagan,Aram Galstyan,Kristina Lerman,Linhong Zhu,Emilio Ferrara,Alessandro Flammini,Filippo Menczer,Andrew Stevens,Alex Dekhtyar,Shuyang Gao,Tad Hogg,Farshad Kooti,Yan Liu,Onur Varol,Prashant Shiralkar,V. G. Vinod Vydiswaran,Qiaozhu Mei,Tim Hwang +20 more
TL;DR: The most recent DARPA Challenge as mentioned in this paper focused on identifying influence bots on a specific topic within Twitter, and three top-ranked teams were identified by the DARPA Social Media in Strategic Communications program.
Journal ArticleDOI
Phase transitions and the search problem
TL;DR: Techniques that were originally developed in statistical mechanics can be applied to search problems that arise commonly in artificial intelligence and predict that abrupt changes in computational cost should occur universally, as heuristic effectiveness or search space topology is varied.
Proceedings ArticleDOI
Enhancing privacy and trust in electronic communities
TL;DR: This work proposes new non-third party mechanisms to overcome barriers to finding shared preferences, discovering communities with shared values, removing disincentives posed by liabilities, and negotiating on behalf of a group.