What is Agent Analyst

1. What is Agent Analyst? Nathan Strout, Naicong Li University of Redlands Redlands, CA USA ESRI International User Conference 2006

2. Agenda What is Agent Based Modeling? What is Agent Analyst? How does Agent Analyst Work? Agent Analyst User Community Bird Migration Sample Model Urban Growth Sample Model

3. What is Agent-Based Modeling and Simulation (ABMS)? ABMS creates electronic laboratories that allow experimentation with simulated complex systems: � using sets of agents and frameworks for simulating the agent�s decisions and interactions � demonstrating how a system could evolve through time, using only a description of the behaviors of the individual agents Focuses on individual (agent) behavior with rules generally based on theories of the individual Enables the study of how system-level and individual-level patterns emerge from rules at the individual level Often used to model complex adaptive systems made up of agents that interact and reproduce while adapting to a changing environment � Economic markets with producers, distributors, and consumers � Social systems with people, groups, factions, and countries � Ecosystems with species, individuals, hives, and flocks ABMS creates electronic laboratories that allow experimentation with simulated complex systems: � using sets of agents and frameworks for simulating the agent�s decisions and interactions � demonstrating how a system could evolve through time, using only a description of the behaviors of the individual agents Focuses on individual (agent) behavior with rules generally based on theories of the individual Enables the study of how system-level and individual-level patterns emerge from rules at the individual level Often used to model complex adaptive systems made up of agents that interact and reproduce while adapting to a changing environment � Economic markets with producers, distributors, and consumers � Social systems with people, groups, factions, and countries � Ecosystems with species, individuals, hives, and flocks

4. What is Agent Analyst? Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps

5. What is Agent Analyst? Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps

6. What is Agent Analyst? Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps

7. How Does Agent Analyst Work? Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps Agents many times make decisions in space Where the agent is and what features are around them influences their decisions Where other agents are relative to processing agent influences the decision making One or more of the behaviors of an agent involves movement Agent�s decisions can be based on spatial analysis that can be derived from a GIS Agents can change the spatial arrangement of things Agent�s decision making changes with the changing landscape ------ You identify objects or agents Animals Terrorists Land parcels Any thing that �makes a decision� or performs an action The agents do things (perform an action or not) Base their decisions on: Their state Interactions with other agents Interactions with the external world Global factors Environment Factors (from surfaces or maps) Scheduler � defines the time steps

8. Agent Analyst User Community

9. Sample Models Bird Migration Model Urban Growth Model Objectives Develop an agent movement model using existing GIS data and analysis from previous studies. Develop an agent state-change model using existing GIS data and analysis from previous studies. Learn and evaluate the modeling capability of Agent Analyst

10. Agent Analyst Bird Migration Sample Model Nathan Strout, Naicong Li, Tim Krantz University of Redlands Redlands, CA USA

11. Salton Sea Bird-Banding Bird locations are tracked when banded, encountered, and recovered by the Bird Banding Laboratory Analysis of banding data was completed by the Salton Sea Database Program at the University of Redlands to study the importance of the Salton Sea to migratory birds. Approximately 20,000 bird banding records Birds recovered from as far away as Russia and Peru 2/3 of all migratory birds in the continental US can be found at the Salton Sea

12. Model Design General Migration Rules: Avoid flying over ocean and other large bodies of water Stop at large lakes to feed Avoid flying over mountain ranges Targets: Pintails Winter � Gulf Coast or Salton Sea Summer � Prairie Pothole Region Geese Winter � Salton Sea or Gulf Coast Summer � Banks Island, ANWR, Arctic North Slope Barometric Pressure South Migration � stay on the left of a low North Migration � stay on the right of a lowBarometric Pressure South Migration � stay on the left of a low North Migration � stay on the right of a low

13. Constraints Data

14. Agent Decision-Making Cellular Automata Evaluates neighboring cells for most suitable Evaluates probability scores for each neighboring cell of each constraint layer Weights all probabilities to assign a master cell probability Apply a random factor to select 1 cell among highest probability cells Moves point agent to the centroid of the selected cell

15. Urban Growth Sample Model with ArcGIS Agent Analyst Naicong Li, Nathan Strout, Aditya Agrawal, Paul Burgess University of Redlands Redlands, CA USA

16. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Demo Model development process

17. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Test the modeling capability of Agent Analyst Develop a rule based urban growth model with suitability parameters and cellular automata flavor (in progress) Data Model design Demo Model development process

18. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Study area of a previous project (1 medium sized city and 2 small towns) 38,000 parcels, 12,000 undeveloped parcels Parcels shape file, raster layers of various constraints and suitability factors, dbf table for parcel neighborhood information Model design Demo Model development process

19. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Parameters considered Agent behavior Model level actions Demo Model development process

20. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Parameters considered Environmental constraints Suitability factors Neighborhood factors Land use policy constraints Suitability parameters with user adjustable weights in scenario building Agent behavior Model level actions Demo Model development process

21. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Environmental constraints Deep slopes (> 20 percent) Rivers and streams (with buffers) Fault lines (with buffers) Flood zones ? Combined into �Hard� constraints layer ? Parcel developability: Buildable area >= minimum required building site area Hard constraints percentage < threshold

22. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Suitability factors Ownership Access to local roads Distance to major roads Distance to town

23. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Suitability factors Ownership Access to local roads Distance to major roads Distance to town

24. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Suitability factors Ownership Access to local roads Distance to major roads Distance to town

25. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Suitability factors Ownership Access to local roads Distance to major roads Distance to town

26. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Neighborhood factors Percentage of developed neighbors Local road access through developed neighbors (up to 2nd order neighbors)

27. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Land use policy constraints - proposed conservation oriented land use policy preserving: Agricultural land Rural living Parks Resource preservation Wild life corridor ? �Soft� constraints ? suitability parameter in scenario building

28. Building an Urban Growth Model with ArcGIS Agent Analyst Model design -- Parameters considered Suitability parameters with user adjustable weights in scenario building: Distance to town Distance to major roads Land use policy constraints

29. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Parameters considered Agent behavior Parcel agent initialization Parcel agent rules applied at each simulation cycle Random factors Model level actions Demo Model development process

30. Building an Urban Growth Model with ArcGIS Agent Analyst Model design � Agent behavior Parcel agent initialization (get information about self) �Hard� constraints area, calculate percentage �Soft� constraints percentage Distance to town Distance to local roads Distance to major roads Initial development status, ownership information already in parcel attributes Calculate adjustable suitability rating in terms of distance to town, distance to major roads, �soft� constraints percentage, and their weights Initialize neighbor list

31. Building an Urban Growth Model with ArcGIS Agent Analyst Model design � Agent behavior Parcel agent rules executed during each simulation cycle (year) Check current development status Check environmental constraints Check ownership Check access to local roads (including accessing through developed neighbors) Check adjustable suitability rating Check percentage of developed neighbors

32. Building an Urban Growth Model with ArcGIS Agent Analyst Model design � Agent behavior Probability random factor applied to Development of public owned parcels Parcel development based on percentage of developed neighbors Getting local road access through developed neighboring parcels

33. Building an Urban Growth Model with ArcGIS Agent Analyst Model design � Model level actions Initialization Initialize housekeeping variables Set environment rasters Initialize parcel agents Record total number of parcels, total number of undeveloped parcels, total number undevelopable parcels based on �hard� environmental constraints Record/calculate upper and lower bounds of adjustable suitability parameters and simulation cycle increments Record neighborhood information for each parcel

34. Building an Urban Growth Model with ArcGIS Agent Analyst Model design � Model level actions End of cycle action Report total number of developed parcels for this cycle Report total number of developed parcels so far Adjust acceptable suitability ratings for the next cycle Other housekeeping actions

35. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Live demo Model development process

37. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Demo Model development process Model design specification Data preparation Model implementation Model testing and calibration Model performance tuning

38. Building an Urban Growth Model with ArcGIS Agent Analyst Model development process � Data preparation Parcel shapefile with information on parcel area, ownership, development status. All other attributes stripped Environment layers, produced by ArcGIS ModelBuilder models, combining factors that are treated the same way (e.g. various hard constraints factors) to reduce input to AA model Python script calling geoprocessing tools to generate parcel neighbor list

39. Building an Urban Growth Model with ArcGIS Agent Analyst

40. Building an Urban Growth Model with ArcGIS Agent Analyst Model development process � Model implementation Start with a very small test area where all or most of factors are present Disable random factor in initial development Test individual parameters by disabling the effect of the others Add parameters and random factors. Test on larger dataset

41. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Demo Model development process Model design specification Data preparation Model implementation Model testing and calibration Adjust threshold values Etc. Model performance tuning

42. Building an Urban Growth Model with ArcGIS Agent Analyst Objective Data Model design Demo Model development process Model design specification Data preparation Model implementation Model testing and calibration Model performance tuning Use undeveloped parcels only (although neighbors list was generated on the bases of all parcels) Reduce the number of rasters Use integer rasters instead of double or float rasters (but�)

43. Building an Urban Growth Model with ArcGIS Agent Analyst Future Work Capacity/demand feedback More detailed development status (high vs. low density, different land use based on zoning) Socioeconomic parameters Population growth (?dwelling units growth) forecast Job opportunity trends Household income trends Property value change trends Etc. Quality of life indicators Access to public transportation Access to services (hospitals, retails, etc.) Access to school Access to park / green space Crime rates Etc. Model validation using historic data

44. Redlands InstituteUniversity of Redlands1200 E. Colton Ave.Redlands, CA 92373909-748-8268www.redlands.edu/redlandsinstitutehttp://www.institute.redlands.edu/agentanalyst/