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Evolving Event-driven Programs with SignalGP

Published in the Proceedings of The 2018 Genetic and Evolutionary Computation Conference (GECCO)

Experiment Configuration Details

This page documents miscellaneous configuration details for experiments from our GECCO 2018 paper, Evolving Event-Driven Programs with SignalGP (Lalejini and Ofria, 2018). A pre-print of this work can be found here: https://arxiv.org/pdf/1804.05445.pdf

See the SignalGP section of our paper for context on SignalGP virtual hardware/program evaluation.

Default SignalGP Instruction Set

Here, we provide details on the default SignalGP instruction set used in this experiment. These instructions are used across both the changing environment and distributed leader election problems.

Relevant abbreviations:

Table of default instructions

Instruction # Arguments Uses Tag? Description
Inc 1 No WM[ARG1] = WM[ARG1] + 1
Dec 1 No WM[ARG1] = WM[ARG1] - 1
Not 1 No WM[ARG1] = !WM[ARG1] Logically toggle WM[ARG1]
Add 3 No WM[ARG3] = WM[ARG1] + WM[ARG2]
Sub 3 No WM[ARG3] = WM[ARG1] - WM[ARG2]
Mult 3 No WM[ARG3] = WM[ARG1] * WM[ARG2]
Div 3 No WM[ARG3] = WM[ARG1] / WM[ARG2] Safe; division by 0 is NOP.
Mod 3 No WM[ARG3] = WM[ARG1] % WM[ARG2] Safe
TestEqu 3 No WM[ARG3] = (WM[ARG1] == WM[ARG2])
TestNEqu 3 No WM[ARG3] = (WM[ARG1] != WM[ARG2])
TestLess 3 No WM[ARG3] = (WM[ARG1] < WM[ARG2])
If 1 No If WM[ARG1] != 0, proceed; else, skip until next Close or EOF
While 1 No If WM[ARG1] != 0, loop; else, skip until next Close or EOF
Countdown 1 No Same as While, but decrements WM[ARG1]
Close 0 No Indicates end of looping or conditional instruction block
Break 0 No Break out of current loop
Call 0 Yes Call function referenced by tag
Return 0 No Return from current function
Fork 0 Yes Calls function referenced by tag on a new thread
SetMem 2 No WM[ARG1] = ARG2
CopyMem 2 No WM[ARG1] = WM[ARG2]
SwapMem 2 No Swap(WM[ARG1], WM[ARG2])
Input 2 No WM[ARG2] = IM[ARG1]
Output 2 No OM[ARG2] = WM[ARG1]
Commit 2 No SM[ARG2] = WM[ARG1]
Pull 2 No WM[ARG2] = SM[ARG1]
Nop 0 No No-operation

Changing Environment Problem

Problem-specific Instructions

Instructions specific to the changing environment problem.

Instruction # Arguments Uses Tag? Description
Terminate 0 No Kill thread Terminate is executed on
SenseEnvState0 1 No WM[ARG1] = 1 if environment in state 0; else, WM[ARG1] = 0
SenseEnvState1 1 No WM[ARG1] = 1 if environment in state 1; else, WM[ARG1] = 0
SenseEnvState2 1 No WM[ARG1] = 1 if environment in state 2; else, WM[ARG1] = 0
SenseEnvState3 1 No WM[ARG1] = 1 if environment in state 3; else, WM[ARG1] = 0
SenseEnvState4 1 No WM[ARG1] = 1 if environment in state 4; else, WM[ARG1] = 0
SenseEnvState5 1 No WM[ARG1] = 1 if environment in state 5; else, WM[ARG1] = 0
SenseEnvState6 1 No WM[ARG1] = 1 if environment in state 6; else, WM[ARG1] = 0
SenseEnvState7 1 No WM[ARG1] = 1 if environment in state 7; else, WM[ARG1] = 0
SenseEnvState8 1 No WM[ARG1] = 1 if environment in state 8; else, WM[ARG1] = 0
SenseEnvState9 1 No WM[ARG1] = 1 if environment in state 9; else, WM[ARG1] = 0
SenseEnvState10 1 No WM[ARG1] = 1 if environment in state 10; else, WM[ARG1] = 0
SenseEnvState11 1 No WM[ARG1] = 1 if environment in state 11; else, WM[ARG1] = 0
SenseEnvState12 1 No WM[ARG1] = 1 if environment in state 12; else, WM[ARG1] = 0
SenseEnvState13 1 No WM[ARG1] = 1 if environment in state 13; else, WM[ARG1] = 0
SenseEnvState14 1 No WM[ARG1] = 1 if environment in state 14; else, WM[ARG1] = 0
SenseEnvState15 1 No WM[ARG1] = 1 if environment in state 15; else, WM[ARG1] = 0
SetState0 0 No Set internal state to 0
SetState1 0 No Set internal state to 1
SetState2 0 No Set internal state to 2
SetState3 0 No Set internal state to 3
SetState4 0 No Set internal state to 4
SetState5 0 No Set internal state to 5
SetState6 0 No Set internal state to 6
SetState7 0 No Set internal state to 7
SetState8 0 No Set internal state to 8
SetState9 0 No Set internal state to 9
SetState10 0 No Set internal state to 10
SetState11 0 No Set internal state to 11
SetState12 0 No Set internal state to 12
SetState13 0 No Set internal state to 13
SetState14 0 No Set internal state to 14
SetState15 0 No Set internal state to 15

Environment-state Tag Associations

In the event-driven and combined treatments for the changing environment problem, environmental changes produce signals that have environment-specific tags. These tags determine which of a program’s functions (if any at all) will be run in response to the signal.

Environment-state Tag (16-bit)
0 0000000000000000
1 1111111111111111
2 1111000000001111
3 0000111111110000
4 1111000011110000
5 0000111100001111
6 0000000011111111
7 1111111100000000
8 0110011001100110
9 1001100110011001
10 1001011001101001
11 0110100110010110
12 0110011010011001
13 1001100101100110
14 1001011010010110
15 0110100101101001

For example, if the environment changes to state 2, an event with the 1111000000001111 tag will be generated. As a result, the function of the program being evaluated with the closest matching tag to 1111000000001111 will be triggered.

Hand-coded Solutions

Here, we give hand-coded SignalGP programs that solve the eight-state changing environment problem.

Event-driven Program

The following program follows the event-driven paradigm and can perfectly solve the eight-state changing environment problem.

Fn- denotes the beginning of a function; the function’s tag follows Fn-. All instructions below a function declaration up until the next function declaration belong to that function. Instructions may be followed by tags given in square brackets, and/or followed by arguments given in parentheses.

Fn−0000000000000000: 
  SetState0

Fn−1111111111111111: 
  SetState1

Fn−1111000000001111: 
  SetState2

Fn−0000111111110000: 
  SetState3

Fn−1111000011110000: 
  SetState4

Fn−0000111100001111: 
  SetState5

Fn−0000000011111111: 
  SetState6

Imperative Program

The following program follows the imperative paradigm. Note that this program cannot solve the changing environment problem perfectly because the resolution of environmental sensing is not fast enough to perfectly track environmental changes at the rate they occur.

Fn- denotes the beginning of a function; the function’s tag follows Fn-. All instructions below a function declaration up until the next function declaration belong to that function. Instructions may be followed by tags given in square brackets, and/or followed by arguments given in parentheses.

Fn−0000000000000000: 
  SetState0
  Fork[0000000000000001] 
  Fork[0000000000000011] 
  Fork[0000000000000111]  
  Fork[0000000000001111] 
  Fork[0000000000011111] 
  Fork[0000000000111111]   
  Fork[0000000001111111] 
  Fork[0000000011111111] 
  SetMem(0 ,1)
  While(0) 
    SenseEnvState0(1) 
    If(1)
      SetState0

Fn−0000000000000001: 
  SetMem(0 ,1)
  While(0)
    SenseEnvState1(1) 
    If(1)
      SetState1

Fn−0000000000000011: 
  SetMem(0 ,1) 
  While(0)
    SenseEnvState2(1) 
    If(1)
      SetState2

Fn−0000000000000111: 
  SetMem(0 ,1) 
  While(0)
    SenseEnvState3(1) 
    If(1)
      SetState3

Fn−0000000000001111: 
  SetMem(0 ,1) 
  While(0)
    SenseEnvState4(1) 
    If(1)
      SetState4

Fn−0000000000011111: 
  SetMem(0 ,1) 
  While(0)
    SenseEnvState5(1) 
    If(1)
      SetState5

Fn−0000000000111111: 
  SetMem(0 ,1) 
  While(0)
    SenseEnvState6(1) 
    If(1)
      SetState6

Fn−0000000001111111: 
  SetMem(0 ,1) 
  While(0)
    SenseEnvState7(1) 
    If(1)
      SetState7

Distributed Leader Election Problem

Problem-specific Instructions

Instructions specific to the distributed leader election problem.

In the distributed leader election problem, each SignalGP agent in a distribute system has a facing attribute that describes the direction the agent is currently facing: Up, Down, Left, or Right.

Instruction # Arguments Uses Tag? Description
RotCW 0 No Rotate clockwise (90 degrees)
RotCCW 0 No Rotate counter-clockwise (90 degrees)
RotDir 1 No Rotate to face direction specified by (WM[ARG1] % 4)
RandomDir 1 No WM[ARG1] is set to a random direction (values 0 through 3)
GetDir 1 No WM[ARG1] is set to the agent’s current orientation
SendMsgFacing 0 Yes Send output memory as message to faced neighbor
BroadcastMsg 0 Yes Broadcast output memory as message to all neighbors
RetrieveMsg 0 Yes Retrieve message from message inbox
GetUID 1 No WM[ARG1] = agent ID
GetOpinion 1 No WM[ARG1] = current vote
SetOpinion 1 No Set current vote to WM[ARG1]

Hand-coded Solutions

Here, we provide hand-coded SignalGP programs for the distributed leader election problem. Each of these programs can successfully reach consensus.

Event-driven solution

Fn−0000000000000000: 
GetUID(0)
SetOpinion(0) 
SetMem(15 ,1) 
While(15)
  GetOpinion (0)
  Output(0 ,0)
  BroadcastMsg(0 ,0 ,0)[1111111111111111]
Close

Fn−1111111111111111: 
  Input(0 ,1) 
  GetOpinion(0) 
  TestLess(1 ,0 ,2)
  If(2) 
    SetOpinion(1)

Imperative (fork-on-retrieve) solution

Fn−0000000000000000: 
  GetUID(0) 
  SetOpinion(0) 
  SetMem(15 ,1) 
  While(15)
    GetOpinion(0)
    Output(0 ,0)
    BroadcastMsg(0 ,0 ,0)[1111111111111111] 
    RetrieveMsg
  Close

Fn−1111111111111111: 
  Input(0 ,1) 
  GetOpinion(0) 
  TestLess(1 ,0 ,2)
  If(2) 
    SetOpinion(1)

Imperative (copy-on-retrieve) solution

Fn−0000000000000000: 
  GetUID(0) 
  GetUID(1) 
  SetOpinion (0) 
  SetMem(15 ,1) 
  While(15)
    GetOpinion (0)
    Output(0 ,0)
    BroadcastMsg(0 ,0 ,0)[1111111111111111] 
    RetrieveMsg
    Input(0 ,1)
    TestLess(1 ,0 ,2)
    If (2) 
      SetOpinion(1)
    Close 
  Close

References

Lalejini, A., & Ofria, C. (2018). Evolving Event-driven Programs with SignalGP. In Proceedings of the Genetic and Evolutionary Computation Conference. ACM. https://doi.org/10.1145/3205455.3205523