Multi-Action Situational Response

by Jason Madden

5/1/2008

Motivation

Autonomous agents used in real world applications

Need methods to control without having to interact with the agents

Can Improvements be made?

The Problem

•What is X-Pilot?

–2-D multi player space combat game.

•What makes X-Pilot a good test bed.

–Finite, simplified( in respect to the physical world) environment

Problem Definition

Direct input Relational Input

Represents a direct readof the state variables

● Velocity

● Direction

● Wall distance

● Enemy distance

Allows knowledge of thedifference between the ship'sdirection and another angle

including:

● target enemy direction

● bullets predicted contact

angle

● enemy's heading

● bullet tracking

● projected firing angle

● and wall structure.

Goal

•To develop a autonomous controller with direct and relational input, that maximizes the time the agent is

alive.•Allowable actions: Thrust, turn, and shoot

Solution Method•Alteration of a GA developed by Matt Parker, Gary Parker and Timothy Doherty.1. Agent is approaching wall and is very close to wall.2. Agent is approaching wall and somewhat close to wall.3. Agent is approaching wall and at a moderate distance from wall.4. Agent is approaching wall at any distance and a bullet is incoming.5. Agent is approaching wall at any distance and an enemy is close and closing.6. Agent is approaching wall at any distance and an enemy is close but not closing.7. Bullet is incoming and very close to striking.8. Enemy is close and incoming bullet is close.9. Enemy is at a medium to far range and incoming bullet is close.10. Enemy is detected medium to close.11. Enemy is detected medium to far.12. Agent is entering a corner clockwise.13. Agent is entering a corner counterclockwise.14. Agent detects no walls, bullets or enemy agents.15. Wall detected 90° to left of agent.16. Wall detected 90° to right of agent.

Solution Method (changes)

•Changing the representation of a gene.

• Inspired from physics and biology

–Add some uncertainty for a situation

Further Implementation Details

Results

0

1

2

3

4

5

6

7

8

9Average Fitness

EA

Bench

Number of fitness evals

Fitn

ess

Maximum Fitness Results

01

23

45

67

89

1011

1213

14

0

5

10

15

20

25

30

Max Fitness this Generation

EA Max Fitness

Generation

Tim

e in

Seconds

Conclusions and Observations

•Evolution is slow•Competitive and Cooperative

•GA method strays away from a self building program.

•Determine a fitness function that prevents the reward for inactivity.

The End!

Questions?

Problem Statement

Given a spaceship within the X-Pilot environment and a set of environmental inputs, create an automated control for the space ship. The inputs include direct input which represent a direct read of the variables used in X-Pilot and relational input. Relational input allows for the comparison of two angles.

This will find the difference between the ship's direction and another angle including target enemy direction, bullets predicted contact angle, enemy's heading, bullet tracking, projected firing angle, and wall structure. The automated control is allowed to turn the ship, thrust, and shoot bullets.

./morton "-join localhost -port 2059" localhost 1444 ""