works
|
about
Behavior Tree Based Simulated
Command and Control
Noah Syrkis
May 21, 2025
1 |
Granular decision making
2 |
Domain Specific Language
1 |
Granular decision making
▶
Control problems are inherently hierarchical
▶
An order from a general commanding the task of a betalion is high-level
▶
In action of each individual solder is not specified there
▶
The simulation strategic encounters has been saturated with deep learning algorithms
▶
[1]
1 of
6
2 |
Domain Specific Language
▶
The domain specific language (DSL) shown in
Table 1
specifies unit behavior
▶
Figure 1
shows the grammat used to specify
behavior
root
→
tree
(
▷
tree
)
⋆
program
tree
→
leaf
|
node
node or leaf
leaf
→
A (
move
|
attack
)
action
|
C (
reachable
)
condition
node
→
S (
root
)
sequence
|
F (
root
)
fallback
move
→
move direction
move action
direction
→
to | from
direction
Table 1: Behavior tree grammar
2 of
6
2 |
Domain Specific Language
F (
A move target |>
S (
C is_alive |> A move target
) |>
A move target,
)
𝑎
𝑡
𝑜
𝑡
𝐹
𝐴
0
𝑆
𝐴
2
𝐶
0
𝐴
1
Figure 1: Behavior tree example (see
Appendix A
for implementation details)
3 of
6
References
[1]
M. Colledanchise and P. Ögren,
Behavior Trees in Robotics and AI: An Introduction
. 2018. doi:
10.1201/9780429489105
.
4 of
6
A |
Trees vs. Arrays
▶
Trees versus arrays
▶
Leaf nodes are actions and conditions
▶
Rest are sequence or fallback combinators
5 of
6
A |
Trees vs. Arrays
index
parent
follows
skips
𝐴
0
F
–
3
𝐶
0
S
S
1
𝐴
1
S
F
1
𝐴
2
F
S
0
𝑎
𝑡
𝑜
𝑡
𝐹
𝐴
0
𝑆
𝐴
2
𝐶
0
𝐴
1
Figure 2: Behavior tree (left) and corresponding behavior array (right)
6 of
6
Behavior Tree Based Simulated
Command and Control
Noah Syrkis
May 21, 2025
1 |
Granular decision making
2 |
Domain Specific Language
1 |
Granular decision making
▶
Control problems are inherently hierarchical
▶
An order from a general commanding the task of a betalion is high-level
▶
In action of each individual solder is not specified there
▶
The simulation strategic encounters has been saturated with deep learning algorithms
▶
[1]
1 of
6
2 |
Domain Specific Language
▶
The domain specific language (DSL) shown in
Table 1
specifies unit behavior
▶
Figure 1
shows the grammat used to specify
behavior
root
→
tree
(
▷
tree
)
⋆
program
tree
→
leaf
|
node
node or leaf
leaf
→
A (
move
|
attack
)
action
|
C (
reachable
)
condition
node
→
S (
root
)
sequence
|
F (
root
)
fallback
move
→
move direction
move action
direction
→
to | from
direction
Table 1: Behavior tree grammar
2 of
6
2 |
Domain Specific Language
F (
A move target |>
S (
C is_alive |> A move target
) |>
A move target,
)
𝑎
𝑡
𝑜
𝑡
𝐹
𝐴
0
𝑆
𝐴
2
𝐶
0
𝐴
1
Figure 1: Behavior tree example (see
Appendix A
for implementation details)
3 of
6
References
[1]
M. Colledanchise and P. Ögren,
Behavior Trees in Robotics and AI: An Introduction
. 2018. doi:
10.1201/9780429489105
.
4 of
6
A |
Trees vs. Arrays
▶
Trees versus arrays
▶
Leaf nodes are actions and conditions
▶
Rest are sequence or fallback combinators
5 of
6
A |
Trees vs. Arrays
index
parent
follows
skips
𝐴
0
F
–
3
𝐶
0
S
S
1
𝐴
1
S
F
1
𝐴
2
F
S
0
𝑎
𝑡
𝑜
𝑡
𝐹
𝐴
0
𝑆
𝐴
2
𝐶
0
𝐴
1
Figure 2: Behavior tree (left) and corresponding behavior array (right)
6 of
6