4 citations · 4 across the 5 of their papers we have counts for
6 papers
Deceptive Stochastic Patrolling via Markov Chain Lifting
Yohan John, Gilberto Diaz-Garcia, Jason R. Marden +1
In this paper we propose lifted Markov Chains (MCs) as a new paradigm for deriving patrol strategies for mobile agents on an environment represented as a graph. Lifted MCs operate…
Incentive Design in Competitive Resource Allocation: Exploiting Valuation Asymmetry in Tullock Contests
Gilberto Diaz-Garcia, Keith Paarporn, Jason R. Marden
In competitive resource allocation, a central coordinator may seek to gain an advantage not by directly controlling subordinate agents, but by strategically manipulating the inform…
The Value of Compromising Strategic Intent in General Lotto Games
Gilberto Diaz-Garcia, Keith Paarporn, Jason R. Marden
Resource allocation in adversarial environments is a fundamental challenge across various domains, from corporate competition to military strategy. This article examines the impact…
Strategic Coalitions in Networked Contest Games
Gilberto Diaz-Garcia, Francesco Bullo, Jason R. Marden
In competitive resource allocation formulations multiple agents compete over different contests by committing their limited resources in them. For these settings, contest games off…
RoSSO: A High-Performance Python Package for Robotic Surveillance Strategy Optimization Using JAX
Yohan John, Connor Hughes, Gilberto Diaz-Garcia +2
To enable the computation of effective randomized patrol routes for single- or multi-robot teams, we present RoSSO, a Python package designed for solving Markov chain optimization…
A Stochastic Surveillance Stackelberg Game: Co-Optimizing Defense Placement and Patrol Strategy
Yohan John, Gilberto Diaz-Garcia, Xiaoming Duan +2
Stochastic patrol routing is known to be advantageous in adversarial settings; however, the optimal choice of stochastic routing strategy is dependent on a model of the adversary.…