PlantMoosePredator System Simulation

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Plant-Moose-Predator System Simulation
Anastasia Mironova CS 470
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Project Overview

• Goal
• Develop an agent-based simulation to model
  plant-moose-predator system behavior
• Client is Dr. Donald Spalinger, Department of
  Biological Sciences, Professor and Chair
• Why
• To assist scientists in codifying current
  hypotheses and axioms regarding the growth and
  defense responses of plants to herbivore foraging
  patterns and foraging efficiency, herbivore
  productivity and habitat carrying capacity, and
  moose-predator interactions
• Limited capabilities of existing systems

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Desirable vs. Possible

• Priority list for the desirable version
• Flexible Design
• 2D Landscape implementation
• Agent Plant implementation
• Agent Moose implementation
• Plant-Moose interaction implementation
• Expansion of scope (space and number of agents)
• Optimization (memory, run-time)
• Agent Predator implementation
• Moose-Predator interaction implementation
• Complex Landscape Patterns
• Artificial Intelligence Behavior Patterns for
  Agents
• Main decision little of everything
• vs. thorough specifics

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Implementation Decisions

• Effort was geared toward more thorough
  implementation of specific components according
  to the initial priority list
• Flexible, reliable system architecture, capable
  of fully supporting all the functional
  specifications known at the time and allowing for
  future expansions
• Emphasized Simulation Components
• Landscape model
• Plants

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Simulation PMPSim.java

• Timer
• Landscape LandscapeSegment
• Plants
• PlantsHashTable Plant, hashkey plantID
• PlantsArray plantID
• Moose
• MooseHashTable Moose, hashkey mooseID
• MooseArray mooseID
• Predators
• PredatorsHashTable Predator, hashkey
  predatorID
• PredatorsArray predatorID
• Other parameters
• GrowthSeason, Precipitation, etc.

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Simplified System Architecture
SimulationParametersMainFrame
SimpleLandscapeSpecificationsPanel
SimulationMainFrame
SimulationMenuBar
AdvancedLandscapeSpecificationsFrame
SimulationToolBar
LandscapeToolBar
IndividualSegmentDisplay
SimplePlantsSpecificationsPanel
SimpleMooseSpecificationsPanel
SimplePredatorsSpecificationsPanel
CustomPlantPropertiesFrame
PresetPlantPropertiesFrame
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GUI Representation of the System
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Landscape Model

• Main design decision
• Partitioning
• Characteristics
• Dimensions
• Elevation Contours
• Bogs/Wetlands
• Forest Habitat
• Riparian Habitat
• Plant species-specific patches
• Custom View

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Plants

• Preset vs. Custom
• Groups vs. Individual
• Characteristics
• Plant ID
• Species Name
• Coordinates
• Elevation Range
• Aspect Preference
• Special Habitat Associations
• Habitat Restrictions

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Potential Extensions

• Existing system design allows for
• Intuitive implementation of any additional types
  of agents, such as
• Moose
• Predators
• Potentially, supporting very high levels of
  complexity, necessary for incorporating extensive
  amounts of research data and, hence, giving the
  simulation the capabilities to represent a more
  realistic model
• Future optimization in both memory usage and
  run-time via
• Landscape partitioning
• Threading

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Conclusion

• Developed a prototype of fundamental components
  for customizing and running plant-moose-predators
  simulations
• Lessons Learned
• More about working with a real client
• More about design
• More about simulations