Show your successful implementation to your TA in class for bonus points (1 or 2). The setup for this tutorial on machines in the lab is to download Intellij Idea (community) and JDK (Linux x64) - (tarball for linux) and extract them in your home folder. Prebuilt windows binaries can be downloaded here
RobotEmilAgent.java
, in method RobotEmilAgent.nextStep(x,y, map)
.
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.
(0, 0)
Action
):
(0, -1)
– Actual effect: 80% NORTH, 10% EAST, 10% WEST
(0, +1)
– Actual effect: 80% SOUTH, 10% EAST, 10% WEST
(+1, 0)
– Actual effect: 80% EAST, 10% NORTH, 10% SOUTH
(-1, 0)
– Actual effect: 80% WEST, 10% NORTH, 10% SOUTH
CellContent
):
Download slightly modified environment. In this environment, using the planning algorithm used in previous task, implement iterative planning from plan failure nodes, the basic step of the Rubust FF:
Report plan failure rate as dependent on the number of passes over steps 2. - 3. using 1000 runs in the environment.
Use class PlanFailure
to report to the simulator failure of the plan.
Use agent method resetAgent()
to restore agent to its original state. You can retain plan from previous simulation runs.
javax.vecmath.Point2i
class to represent a pair of integers.
RobotEmilCreator.java
by changing the constant SIMULATION_STEP_DELAY
, which represents the delay between two actions in miliseconds.