Tech Briefs Stochastic Surveillance and Distributed Coordination Designing fast and unpredictable motion strategies for robotic surveillance agents in complex environments using Markov chain modeling and optimization methods. Air Force Research Laboratory, Arlington, Virginia T his research focused on robotic surveillance in complex environments via autonomous vehicles. The chief aim was to design fast and unpredictable motion strategies for surveillance agents. The technical approach focused on Markov chain modeling and optimization methods. For the setting of faults or randomly appearing intruders, quickest detection algorithms were proposed and the socalled hitting time of both a single and multiple Markov chains were computed and optimized. For example, the meeting time between a pursuer and evader performing random walks was analyzed on digraphs. The closed-form expression for the expected meeting time was obtained and the minimization problem for the expected capture time for a pursuer/evader pair was set up and studied. On the topic of unpredictable strategies, two notions of entropy for robotic motion were proposed. First, the problem of maximizing the entropy rate generated by a random walk was studied. That showed the equivalence to a semidefinite program for reversible chains. Next came the introduction of a novel concept of unpredictability based on the average entropy of the return time variables at the environment locations. This optimization problem was formally studied and validated the performance of projected gradient algorithms for this problem. The algorithms were validated on basic and random graphs and on a publicly available dataset describing crime statistics in San Francisco. The Matlab and Julia implementations of the proposed algorithms were distributed in an open source " RoboSurv " library available on GitHub. The research also provided partial support for work by the PI on a network systems book and a few related topics, including synchronization in pulse-coupled oscillators, graph-theoretic small gain theorems for Aerospace & Defense Technology, June 2021 Free Info at http://info.hotims.com/79414-772 33 Cov ToChttp://info.hotims.com/79414-772 http://info.hotims.com/79414-772 http://www.abpi.net/ntbpdfclicks/l.php?202106ADTNAV