SELF-ORGANIZED STRUCTURES: MODELING POLISTES DOMINULA NEST CONSTRUCTION WITH SIMPLE RULES

Authors' Affiliations

Matthew Harrison(1), Istvan Karsai(2), and Christopher Wallace(1) (1)Department of Computing, College of Business and Technology, East Tennessee State University, Johnson City, TN (2)Department of Biological Sciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN

Location

BAYS MTN. ROOM 125

Start Date

4-4-2018 10:00 AM

End Date

4-4-2018 10:15 AM

Name of Project's Faculty Sponsor

Christopher Wallace

Faculty Sponsor's Department

Department of Computing

Classification of First Author

Graduate Student-Master’s

Type

Oral Presentation

Project's Category

Engineering and Technology

Abstract or Artist's Statement

The self-organized nest construction behaviors of European paper wasps (Polistes dominula) show potential for adoption in artificial intelligence and robotic systems where centralized control proves challenging. However, P. dominula nest construction mechanisms are not fully understood. The goal of this research was to investigate how P. dominula nest structures stimulate worker actions. Simulation utilities were constructed in C++, C#, and Python. Two models from previous work, a three-dimensional model with weighted actions and a two-dimensional model with simple rule-based actions, were combined in a three-dimensional model with simple rules. Nest construction was simulated with a random selection rule, an age-based rule, a height requirement rule, and a height difference rule. Real and idealized nest data were used to evaluate simulated nests. Structures generated with age- and height-based rules showed more correlation with real and idealized nest structures than randomly-generated structures.

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Apr 4th, 10:00 AM Apr 4th, 10:15 AM

SELF-ORGANIZED STRUCTURES: MODELING POLISTES DOMINULA NEST CONSTRUCTION WITH SIMPLE RULES

BAYS MTN. ROOM 125

The self-organized nest construction behaviors of European paper wasps (Polistes dominula) show potential for adoption in artificial intelligence and robotic systems where centralized control proves challenging. However, P. dominula nest construction mechanisms are not fully understood. The goal of this research was to investigate how P. dominula nest structures stimulate worker actions. Simulation utilities were constructed in C++, C#, and Python. Two models from previous work, a three-dimensional model with weighted actions and a two-dimensional model with simple rule-based actions, were combined in a three-dimensional model with simple rules. Nest construction was simulated with a random selection rule, an age-based rule, a height requirement rule, and a height difference rule. Real and idealized nest data were used to evaluate simulated nests. Structures generated with age- and height-based rules showed more correlation with real and idealized nest structures than randomly-generated structures.