Lab11 - Game Theory in Robotics

Motivations and Goals
Become familiar with pursuit-evasion scenario
Be able to establish a greedy policy for pursuit-evasion problem
Tasks (teacher)
Implement and verify the functionality of greedy policy for pursuit-evasion problem (2 points)
Lab resources
Lab sripts: lab11 resource files

Pursuit Evasion

A problem in computer science where a set of pursuers is trying to catch a set of evaders.

Greedy Policy

In greedy policy the next-best state is selected in each discrete step of the game simulation without considering longer prediction horizon.
Usual policies incorporate distances between individual agents as follows:

  • For evaders select the most distant node to all pursuers
  • For pursuers select the closest node to the closest evader

Tasks (2 points) - Lab11G

  1. Implement a greedy policy according to the above-described rules
  2. Note, you can improve the performance of the algorithm by employing more efficient distance function calculation method (e.g. Floyd-Warshall)
  3. Submit archived player.py and planner.py classes into the BRUTE upload system
courses/b4m36uir/labs/lab11.txt · Last modified: 2018/09/06 14:06 (external edit)