based on article and code by M. Tim Jones

This code example examines a game character's current conditions and selects an action accordingly.

The four inputs represent:
• health status (2 = healthy, 1 = minor injuries, 0 = major injuries)
• has a knife (1 = yes, 0 = no)
• has a gun (1 = yes, 0 = no)
• number of enemies present

The four outputs represent the game characters action:
• wander
• attack
• hide
• run

The four inputs (shown in results from left to right) represent:
• health status (2 = healthy, 1 = minor injuries, 0 = major injuries)
• has a knife (1 = yes, 0 = no)
• has a gun (1 = yes, 0 = no)
• number of enemies present

Network is 100.000% correct.

2-1-1-1 Action: Attack
1-1-1-2 Action: Hide
0-0-0-0 Action: Wander
0-1-1-1 Action: Hide
2-0-1-3 Action: Hide
2-1-0-3 Action: Hide
0-1-0-3 Action: Run

In this run, the last pattern wasn't correctly classified.

0.0	0.0	1.0	2.0	Actual: Hide	Expected: Run

0.0	1.0	0.0	2.0	Actual: Hide	Expected: Run

Network is 88.889% correct.

2-1-1-1 Action: Attack
1-1-1-2 Action: Hide
0-0-0-0 Action: Wander
0-1-1-1 Action: Hide
2-0-1-3 Action: Hide
2-1-0-3 Action: Hide
0-1-0-3 Action: Hide

Note that even though the network wasn't perfectly trained, it still managed (by chance) to deliver adequate decisions.

0.0	0.0	0.0	1.0	Actual: Run	Expected: Hide

Network is 94.444% correct.

2-1-1-1 Action: Attack
1-1-1-2 Action: Hide
0-0-0-0 Action: Wander
0-1-1-1 Action: Hide
2-0-1-3 Action: Hide
2-1-0-3 Action: Hide
0-1-0-3 Action: Run