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Code for the paper "Counter-example Guided Learning of Bounds on Environment Behavior" Platform: Matlab Prerequisite: Cplex, S-Taliro, Gurobi, qpOASES To reproduce the result for the two robot problem, run 'robot_falsification' To reproduce the result for the lane change problem, run 'LC_falsification' Index of important functions: params.m: Declaring parameters SVM_reactive_bound.m: Main SVM function that generates the classifier extract_reactive_bound_2region_soft_bdry.m: Generate reactive bound function from the classifier BlackBoxMPCLaneChange.m: Lane change simulator two_robot_sim.m: Simulation of the two robot example to generate positive data two_robot_staliro_shortest_time_reactive.m: S-Taliro file to generate negative data for the two robot example lane_change_staliro.m: S-Taliro file to generate negative data for the lane change example
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Reactive modelling of the environment behavior for robotic systems with falsification and SVM
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