Internal Coherence Verification
In this section we describe simulative experiments settled to assess the internal coherence of the proposed agent-based model and we discuss simulation results. The experiments are settled to be confirmative. The calibration of the model is work in progress and will be completed in the following steps of the research.
Parameters Setting
The verification of logical internal coherence of the model is based on the assumptions derived from current body of knowledge on innovation systems framed as complex learning systems. In particular, we settled 12 different experiments (see Tables 3,4, 5, 6 and 7). In order to ensure the robustness of the results we performed
Table 3 Fixed parameters
|
Fixed parameters |
Values |
|
Competence (c) |
Random |
|
Noise (n) |
10% |
|
Length of message (l) |
50 |
|
Acceptance-threshold |
80% |
|
Number of agents |
50 |
|
Max-ticks |
10,000 |
|
Runs |
30 |
Table 4 Parameters setting to test the behaviour of a high specialized system in a dynamic environment
|
Parameters |
I SET |
II SET |
III SET |
|
Capacity of Exploration (p) |
0.1 |
0.5 |
0.9 |
|
Scope (s) |
0.5 |
||
|
Volatility (v) |
0.2 |
Table 5 Parameters setting to test the behaviour of a high specialized system in a static environment
|
Parameters |
IV SET |
VSET |
VI SET |
|
Capacity of Exploration (p) |
0.1 |
0.5 |
0.9 |
|
Scope (s) |
0.5 |
||
|
Volatility (v) |
0.8 |
Table 6 Parameters setting to test the behaviour of a low specialized system in a dynamic environment
|
Parameters |
VII SET |
VIII SET |
IX SET |
|
Capacity of Exploration (p) |
0.1 |
0.5 |
0.9 |
|
Scope (s) |
0.8 |
||
|
Volatility (v) |
0.2 |
Table 7 Parameters setting to test the behaviour of a low specialized system in a static environment
|
Parameters |
X SET |
XI SET |
XII SET |
|
Capacity of Exploration (p) |
0.1 |
0.5 |
0.9 |
|
Scope (s) |
0.8 |
||
|
Volatility (v) |
0.8 |
- 30 runs for each experimental set. The 12 experiments are performed changing the values of the following parameters:
- • The volatility v of the Competitive Environment CE: (v = 0.2 and 0.8)
- • The exploration capability p of the ICAs: (p = 0.1, 0.5 and 0.9)
- • The level of specialization s of ICAs: (s = 0.5 and 0.8)
Other parameters remain fixed according to the values of the Table 3.
Table 8 The output variables of simulations
|
Output variable |
Description |
|
Surviving ICAs (%) |
Average (on 30 runs) number of surviving ICAs at the end of simulation as percentage of initial population |
|
Average number of surviving Frames of ICAs |
Average (on 30 runs) number of Frames in the individual memories of ICAs, calculated for each new market cycle (for each new message/Regularity provided by the CE) |
|
Collective Interpretations’ dimension |
Total number (on 30 runs) of Individual Interpretations contributing to successful Collective Interpretations |
|
Mean Delta Budget in the system |
Average (on 30 runs) value of the difference between the final budget of the system and the sum of initial budgets attributed to ICAs populating it at the beginning of simulation |
