Abstract
We are interested in identifying the learning status of the social behavioral tasks in the rhesus monkey. In addition, we define the characteristic of stimulus with a numerical quantification. We allow monkeys to interact with individuals of different social status, while we monitor the viewer monkey's behavior by tracking its scan paths. With these observations, we can understand the learning status of this animal via looking behavior analysis on the stimulus. First, the viewer monkey shows different looking patterns among six different classes. Therefore, we can generate different data descriptors of these classes and observe the classification performance of the machine learning algorithm. Second, we design the ground truth model based on the characteristic of each stimulus. We define the distribution of information from the ratio of the face, body, and background area in the stimulus. Lastly, we link them to figure out whether the viewer monkey learned enough about the information in the stimulus.
Original language | English (US) |
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Pages (from-to) | 643-653 |
Number of pages | 11 |
Journal | Simulation Series |
Volume | 53 |
Issue number | 2 |
State | Published - 2021 |
Event | 2021 Annual Modeling and Simulation Conference, ANNSIM 2021 - Virtual, Online Duration: Jul 19 2021 → Jul 22 2021 |
Keywords
- Behavioral and Social Data Analysis
- Learning Status Decision
- Learning Task Modeling
- Looking Behavior Analysis
- Looking Pattern Analysis
ASJC Scopus subject areas
- Computer Networks and Communications