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Figure 5. Mean interaction for an average run with the interaction cost = 0.01 and payoff = 0.05.

Figure 5 Mean interaction for an average run with the interaction cost = 0.01 and payoff = 0.05.

Related Figures (15)

Figure 1. Iterative agent-based model.
Figure 1. Iterative agent-based model.
Figure 1. Mean fitness for an average run of the model with the fitness change rate = 0.01, the cost of interaction = 0.01, and the payoff = 0.01. The initial hypothesis of this model was that the mean interaction rate would increase as the cost of interaction remained low and the payoff for each generation increased. Unfortunately, this hypothesis was proven to be faulty. Fig. 4 — Fig. 8 show that the mean interaction rate remains within a bounded constant region regardless of the cost of interaction and the amount of payoff. The results for runs where the fitness change rate remained constant at 0.05 are presented in Fig. 4 — Fig. 8.
Figure 1. Mean fitness for an average run of the model with the fitness change rate = 0.01, the cost of interaction = 0.01, and the payoff = 0.01. The initial hypothesis of this model was that the mean interaction rate would increase as the cost of interaction remained low and the payoff for each generation increased. Unfortunately, this hypothesis was proven to be faulty. Fig. 4 — Fig. 8 show that the mean interaction rate remains within a bounded constant region regardless of the cost of interaction and the amount of payoff. The results for runs where the fitness change rate remained constant at 0.05 are presented in Fig. 4 — Fig. 8.
Figure 3. Mean agent resource for an average run of the model with the fitness change rate = 0.01, the cost of interaction = 0.01, and the payoff = 0.01.
Figure 3. Mean agent resource for an average run of the model with the fitness change rate = 0.01, the cost of interaction = 0.01, and the payoff = 0.01.
Figure 4. Mean interaction for an average run with cost of interaction = 0.01 and the payoff = 0.01.
Figure 4. Mean interaction for an average run with cost of interaction = 0.01 and the payoff = 0.01.
Figure 6. Mean interaction for an average run with the interaction cost = 0.01 and the payoff = 0.0.10. Modeling an Innovation Ecosystem with Adaptive Agents
Figure 6. Mean interaction for an average run with the interaction cost = 0.01 and the payoff = 0.0.10. Modeling an Innovation Ecosystem with Adaptive Agents
Figure 7. Mean interaction for an average run with the interaction cost = 0.01 and payoff = 0.20.
Figure 7. Mean interaction for an average run with the interaction cost = 0.01 and payoff = 0.20.
Figure 8. Mean interaction for an average run with the interaction cost = 0.01 and the payoff = 0.50.
Figure 8. Mean interaction for an average run with the interaction cost = 0.01 and the payoff = 0.50.
Figure 9. Mean resources for an average run with the interaction cost = 0.01 and the payoff = 0.01
Figure 9. Mean resources for an average run with the interaction cost = 0.01 and the payoff = 0.01
Figure 10. Mean resources for an average run with the interaction cost = 0.01 and the payoff = 0.50.
Figure 10. Mean resources for an average run with the interaction cost = 0.01 and the payoff = 0.50.
Figure 11. Mean interaction for an average run with thefitness rate of change = 0.01 Modeling an Innovation Ecosystem with Adaptive Agents
Figure 11. Mean interaction for an average run with thefitness rate of change = 0.01 Modeling an Innovation Ecosystem with Adaptive Agents
igure 13. Mean interaction for an averagerun with the fitnessrate of change = 0.50. Figure 12. Mean resources for an average run with the fitness of rate change = 0.01.
igure 13. Mean interaction for an averagerun with the fitnessrate of change = 0.50. Figure 12. Mean resources for an average run with the fitness of rate change = 0.01.
Figure 14. Mean resources for an averaged run with the fitness rate of change = 0.50.
Figure 14. Mean resources for an averaged run with the fitness rate of change = 0.50.
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