Artificial God Optimization - a Creation

: Nature Inspired Optimization Algorithms have become popular for solving complex Optimization problems. Two most popular Global Optimization Algorithms are Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). Of the two, PSO is very simple and many Research Scientists have used PSO to solve complex Optimization Problems. Hence PSO is chosen in this work. The primary focus of this paper is on imitating God who created the nature. Hence the term "Artificial God Optimization (AGO)" is coined in this paper. AGO is a new field which is invented in this work. A new Algorithm titled "God Particle Swarm Optimization (GoPSO)" is created and applied on various benchmark functions. The World's first Hybrid PSO Algorithm based on Artificial Gods is created in this work. GoPSO is a hybrid Algorithm which comes under AGO Field as well as PSO Field. Results obtained by PSO are compared with created GoPSO algorithm. A list of opportunities that are available in AGO field for Artificial Intelligence field experts are shown in this work.


Introduction
John Henry Holland proposed Genetic Algorithms in 1970's.From the above answer we can find that many Nature Inspired Optimization algorithms are proposed in literature till date.But there is not even a single algorithm which takes God (who created the nature) as Inspiration for creating innovative optimization algorithms.Hence a new field titled "Artificial God Optimization (AGO)" is invented in this work.AGO field is defined as follows: Artificial Birds are the basic entities in Particle Swarm Optimization algorithm.Similarly, Artificial Gods are the basic entities in Artificial God Optimization (AGO).All the optimization algorithms which are proposed based on Artificial Gods will come under AGO Field.Each Artificial God corresponds to a point in search space.In addition to Artificial Gods there can be Artificial non-Gods in the population.Each Artificial non-God corresponds to a point in the search space.Artificial non-Gods are less powerful than Artificial Gods.Details related to God can be found in Ancient Hindu Religious Texts [1][2].AGO Field concepts are applied to Particle Swarm Optimization (PSO) algorithm to create New AGO Field algorithms.PSO field details are given in articles [3][4][5][6][7][8][9].Articles [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] show details related to Hybrid PSO Algorithms that are created by modifying PSO algorithm.Till date, there are no Artificial God Optimization Algorithms (AGO Algorithms) proposed in literature.This work makes use of this research gap and invents AGO field.
The rest of the article is organized as follows: Particle Swarm Optimization algorithm is shown in Section 2. Section 3 shows "God Particle Swarm Optimization (GoPSO)".Results are explained in Section 4. Opportunities that are present in AGO Field are shown in Section 5. Conclusions are given in Section 6.

Particle Swarm Optimization
Particle Swarm Optimization (PSO) was proposed by Kennedy and Eberhart in 1995.PSO is based on Artificial Birds.It has been applied to solve complex optimization problems.
In PSO, first we initialize all particles as shown below.Two variables pbesti and gbest are maintained.pbesti is the best fitness value achieved by i th particle so far and gbest is the best fitness value achieved by all particles so far.Lines 4 to 11 in the below text helps in maintaining particle best and global best.Then the velocity is updated by rule shown in line no.14.Line 15 updates position of i th particle.Line 19 increments the number of iterations and then the control goes back to line 4.This process of a particle moving towards its local best and also moving towards global best of particles is continued until termination criteria will be reached.

God Particle Swarm Optimization
The basic entities in the God Particle Swarm Optimization (GoPSO) are Artificial Gods and Artificial non-Gods.Gods can always move in the search space.Whereas non-Gods can move in the search space only if non-God receives blessings of Gods.Based on random number generated and GodProbability, the particle is classified into either Artificial non-God or Artificial God.If a particle is classified as Artificial God then it will update position and velocity irrespective of anything.If particle is classified as Artificial non-God then there are two cases.Based on random number generated and BlessingsOfGodProbability the particle is classified into Blessed non-God or not blessed non-God.Blessed non-God can move in search space and hence updates velocity and position.Not Blessed non-God cannot move in search space and hence doesn't update velocity and position.
If the random number generated in line number 13 is less than GodProbability then particle is classified as Artificial God else it is classified as Artificial non-God.Lines 14-17 are executed by God.Lines 19-26 are executed by non-God.If the random number generated is less than BlessingsOfGodProbability then the non-God is blessed else it is not blessed non-God.Blessed non-God executes lines 20-23.Hence velocity and position are updated for Blessed non-God.Line number 25 is blank.Hence Not Blessed non-God is blocked and does nothing.The same procedure is repeated for all particles in first generation.
In second generation, line number 13 is again executed.Particle classified as God in first generation can be classified as non-God in second generation.Particle classified as non-God in first generation can be classified as God in second generation.Similarly, in second generation, line number 19 is again executed.So, whether non-God receives blessings of God or not is dependent on the random number generated and BlessingsOfGodProbability. The remaining procedure is same as that of first generation.

Results
Benchmark Functions used in this paper are taken from [29].The proposed God Particle Swarm Optimization (GoPSO) is applied on five benchmark functions.Results obtained are compared with PSO.

Interesting Opportunities in Artificial God Optimization Field
The following are the opportunities in Artificial God Optimization field (AGO field) for experts in Artificial Intelligence field: From 1970's to till date, there are hundreds of Nature Inspired Optimization Algorithms proposed in literature.A Research scientist asked on Researchgate the following question in March 2015: "Question: What are the various Nature Inspired Optimization Algorithms?" Another Research Scientist replied the following algorithms as answer to the above question: Answer: "The following is the list of various Nature Inspired Optimization Algorithms: Colony Optimization Algorithm (ACO) 8. Cultural Algorithms (CA) 9. Particle Swarm Optimization (PSO) 10.Self-propelled Particles 11.Differential Evolution (DE) 12. Bacterial Foraging Optimization 13.Harmony Search (HS) 14.MBO: Marriage in Honey Bees Optimization 15.Artificial Fish School Algorithm 16.Bacteria Chemotaxis (BC) Algorithm 17. Social Cognitive Optimization (SCO)

Table 1 . Overall Result InTable 1
Green represents Performed well.Red represents didn't performed well.Blue represents performed between well and not well.From Table1we can see that both GoPSO and PSO performed well on all benchmark functions.
Artificial God Optimization field (AGO field) is invented in this work.A novel God Particle Swarm Optimization (GoPSO) is created in this work.PSO and GoPSO performed well on all benchmark functions.The invented AGO field comes under Artificial God Computing Field.As mentioned in arXiv pre-print, arXiv: 1903.12011[cs.NE], there is scope for many PhD's and PostDoc's in Artificial Human Optimization field.It is also mentioned that there are millions of articles possible in AHO field.Similarly, we can easily prove that AGO field invented in this work has millions of opportunities which are yet to be explored by Research Scientists across the globe.