====== Robot Emil 1 ====== ===== Task ===== * Download {{:courses:a4m36pah:robot-emil-1.zip|Emil 1}} * Implement agent to control robot Emil (visualized as blue filled circle) in an environment with obstacles (visualized as gray boxes) and stochastic action execution so that it reaches the cell with gold (visualized as yellow filled circle). * Use **FF-replan** strategy with the most-likely-effect determinization strategy. Plan the path for the robot assuming that all actions will yield the most likely outcome. Execute the plan and monitor the if the action execution behaves as planned. If we detect that one of the action resulted in a different outcome than we planned, replan from the current state to the goal. Repeat until the goal is reached. * Your code should be implemented in ''RobotEmilAgent.java'', in method ''RobotEmilAgent.nextStep(x,y,step''). ===== Evaluation ===== * Run ''RobotEmilCreator'' to simulate the execution of the robot. In fact, 10 simulations with different random seeds will be executed. You need to successfully reach the goal in all simulations to pass. * The simulation finishes as unsuccessful after 200 steps. ===== Environment ===== * Robot starts at (0,0) * Robot can execute following actions with stochastic effects (class ''Action''): * NORTH -- Actual effect: 80% NORTH, 10% EAST, 10% WEST * SOUTH -- Actual effect: 80% SOUTH, 10% EAST, 10% WEST * EAST -- Actual effect: 80% EAST, 10% NORTH, 10% SOUTH * WEST -- Actual effect: 80% WEST, 10% NORTH, 10% SOUTH * The environment is a matrix 20x20, where the first index represents columns (x-coordinate) and the second index represents rows (y-coordinate). The columns (rows) are indexed starting from 0, i.e. we have columns (rows) 0,1,...,19. * Each cell can contain (class ''CellContent''): * EMPTY * OBSTACLE * GOLD ===== Tips & Tricks ===== * You can use ''javax.vecmath.Point2i'' class to represent a pair of integers. * You can speed-up/slow-down the simulation on line 139 in ''RobotEmilCreator.java'' by changing the third parameter of simulate method, which represents the delay between two actions in miliseconds.