Agent based modeling of risk sensitivity and decision making on coalitions

• US 8,057,235 B2
• Filed: 08/12/2005
• Issued: 11/15/2011
• Est. Priority Date: 08/12/2004
• Status: Expired due to Fees

• Current Assignee: Purdue Research Foundation (Purdue University)
• Original Assignee: Purdue Research Foundation (Purdue University)
• Inventors: Sedlmeyer, Robert Louis, Kuznar, Lawrence Anthony, Frederick, William George
• Primary Examiner(s): Gishnock; Nikolai A
• Application Number:
  US11/203,060
• Publication Number:
  US 20060059113A1
• Time in Patent Office: 2,286 Days
• Field of Search: 434/236, 703/14, 706/13, 705/37, 463/1
• US Class Current: 434/236
• CPC Class Codes: G06N 3/004 Artificial life, i.e. computing arrangements simulating life
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

An agent based model system provides simulation of the influence of environmental variables and tendencies in individual and social decision making relating to the formation of coalitions and ethnic groups. The system is based on improved understandings of human decision making under risk, and incorporates recent theoretical developments and computational tools. The system gives analysts the ability to predict the development of coalitions and ethnic groups, as well as the ability to manage the behavior of individuals in such groups. The model results provide confidence intervals for various possible scenarios in a mix of agents'"'"' decision rules and distribution of environmental resources. Applications include management of ethnic groups and violent conditions in unstable nations, the tracking of terrorist organizations, development of coalitions and oligopolies in business, and the modeling and interdiction of criminal organizations.

Claims

1. A method in a parallel processing computer system for simulating individual and social behavior, comprising:

creating a neighborhood of cells;

allocating resources to the cells;

assigning an agent to each cell;

selecting one of a plurality of decision rules for interactions between agents, wherein one of the plurality of decision rules includes a coordination game;

analyzing risk sensitivity using an analytical function W(x)=e^{(d+ax+c sin(bx))}, where a>

bc;

iteratively conducting discrete interactions between the agents using the selected decision rule and allocated resources, wherein the discrete interactions of a first subset of the agents are conducted on a first computing device of the parallel processing computer system and the discrete interactions of a second subset of the agents are conducted on a second computing device of the parallel processing computer system; and

recording interaction outcome.

2. The method of claim 1, wherein the coordination game includes a mixed strategy matrix of:

3. The method of claim 2, wherein R=5, P=3, T=3, and S=0.

4. The method of claim 2, wherein R, P, T, and S are modified with small increases and decreases for payoff sensitivity analysis.

5. The method of claim 2, wherein P=3, T=3, S=0, and R is a random variable ≧

3.

6. The method of claim 1, wherein one of the plurality of decision rules includes a conformist strategy.

7. The method of claim 1, wherein one of the plurality of decision rules includes a prestige-bias strategy.

8. The method of claim 1, wherein one of the plurality of decision rules includes a modified risk posture based on at least one of a sigmoid and an expo-sigmoid function for distribution of resources among agents.

9. The method of claim 1, wherein allocating resources includes uniformly allocating resources to the cells.

10. The method of claim 1, wherein allocating resources includes allocating resources according to a function of a data set, the function including at least one of a sigmoid and an expo-sigmoidal function derived from Fourier signature analysis fit of residuals from at least one of a linear regression to the data set and a logarithm of the data set.

11. The method of claim 1, wherein the one of the plurality of decision rules includes a join probability according to a function of a data set, the function including at least one of a sigmoid and an expo-sigmoidal function derived from Fourier signature analysis fit of residuals from at least one of a linear regression to the data set and a logarithm of the data set.

12. The method of claim 1, wherein at least one of the resources and the one of a plurality of decision rules includes a function of a data set, the data set including a measure of at least one of well-being, social status, and social worth.

13. The method of claim 12, wherein the measure of at least one of well-being, social status, and social worth includes a measure of at least one of demographic data, income, net worth, wealth, personal property ownership, real estate ownership, social prestige, mortality, morbidity, marital status, family status, sex, age, education, health, literacy, human development index, geography, environmental factors, movement, communication, informational constraints, mass media, infrastructure, social services, materials, conflict, peacekeeping forces, provocateurs, influential agents, risk sensitivity, cultural norms, ethnic affiliation, ideological affiliation and kinship.

14. The method of claim 12, further comprising analyzing recorded interaction outcome.

15. The method of claim 14, wherein analyzing recorded interaction outcome includes determining an effect on risk sensitivity of the measure of at least one of well-being, social status, and social worth.

16. The method of claim 14, wherein analyzing recorded interaction outcome includes determining at least one of an individual'"'"'s likelihood of taking a risk, a distribution of well-being, a distribution of social status, a distribution of social worth, a potential for social unrest due to wealth inequalities, an impact of nepotism on social unrest, an influence of class origin of insurgency members, and an influence of class origin and terrorist recruitment.

17. The method of claim 1, wherein creating a neighborhood includes mapping a grid onto a sphere, thereby providing eight neighboring cells for each cell.

18. The method of claim 1, wherein iteratively conducting discrete interactions includes one agent interacting with multiple agents in a single iteration.

19. The method of claim 1, wherein iteratively conducting discrete interactions includes an agent interacting with a non-neighboring agent.

20. The method of claim 1, wherein recording interaction outcome includes recording coalition dynamics, including at least one of coalitions, coalition size, join count, total resources, and coalition locations.

21. The method of claim 1, further comprising collecting a predetermined measure of resources from each agent after conducting each discrete interaction between the agents.

22. The method of claim 1, further comprising displaying Fourier transform of at least one of coalition size and join count.

23. A non-transitory, computer-readable medium having machine-executable code for simulating the interactions of agents, comprising:

code for creating a neighborhood of cells;

code for allocating resources to the cells;

code for assigning an agent to each cell;

code for selecting one of a plurality of decision rules for interactions between agents, wherein one of the plurality of decision rules includes a coordination game;

code for analyzing risk sensitivity using an analytical function W(x)=e^{(d+ax+c sin(bx))}, where a>

bc;

code for iteratively conducting discrete interactions between the agents using the selected decision rule and allocated resources; and

code for recording interaction outcome.

24. The non-transitory, computer-readable medium of claim 23, wherein the coordination game includes a mixed strategy matrix of:

25. The non-transitory, computer-readable medium of claim 23, wherein one of the plurality of decision rules includes a conformist strategy.

26. The non-transitory, computer-readable medium of claim 23, wherein one of the plurality of decision rules includes a prestige-bias strategy.

27. The non-transitory, computer-readable medium of claim 23, wherein one of the plurality of decision rules includes a modified risk posture based on at least one of a sigmoid and an expo-sigmoid function for distribution of resources among agents.

28. The non-transitory, computer-readable medium of claim 23, wherein allocating resources includes allocating resources according to a function of a data set, the function including at least one of a sigmoid and an expo-sigmoidal function derived from Fourier signature analysis fit of residuals from at least one of a linear regression to the data set and a logarithm of the data set.

29. The non-transitory, computer-readable medium of claim 23, wherein the one of the plurality of decision rules includes a join probability according to a function of a data set, the function including at least one of a sigmoid and an expo-sigmoidal function derived from Fourier signature analysis fit of residuals from at least one of a linear regression to the data set and a logarithm of the data set.

30. The non-transitory, computer-readable medium of claim 23, wherein at least one of the resources and the one of a plurality of decision rules includes a function of a data set, the data set including a measure of at least one of well-being, social status, and social worth.

31. The non-transitory, computer-readable medium of claim 23, further comprising code for analyzing recorded interaction outcome.

32. The non-transitory, computer-readable medium of claim 31, wherein the analyzing recorded interaction outcome includes determining an effect on risk sensitivity of the measure of at least one of well-being, social status, and social worth.

33. The non-transitory, computer-readable medium of claim 31, wherein analyzing recorded interaction outcome includes determining at least one of an individual'"'"'s likelihood of taking a risk, a distribution of well-being, a distribution of social status, a distribution of social worth, a potential for social unrest due to wealth inequalities, an impact of nepotism on social unrest, an influence of class origin of insurgency members, and an influence of class origin and terrorist recruitment.

34. The non-transitory, computer-readable medium of claim 23, wherein creating a neighborhood includes mapping a grid onto a sphere, thereby providing eight neighboring cells for each cell.

35. The non-transitory, computer-readable medium of claim 23, wherein iteratively conducting discrete interactions includes one agent interacting with multiple agents in a single iteration.

36. The non-transitory, computer-readable medium of claim 23, wherein iteratively conducting discrete interactions includes an agent interacting with a non-neighboring agent.

37. The non-transitory, computer-readable medium of claim 23, wherein recording interaction outcome includes recording coalition dynamics, including at least one of coalitions, coalition size, join count, total resources, and coalition locations.

38. The non-transitory, computer-readable medium of claim 23, further comprising code for collecting a predetermined measure of resources from each agent after conducting each discrete interaction between the agents.