Robot Emil 1


  • Download 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, in method RobotEmilAgent.nextStep(x,y,step).


  • 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.


  • 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 20×20, 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
    • 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 by changing the third parameter of simulate method, which represents the delay between two actions in miliseconds.
courses/pui/assignments/emil1.txt · Last modified: 2018/02/12 09:41 (external edit)