Velo: Exploring Animal Behavior Modeling through Hybrid Robotics-Simulation Learning Experience
Pages 701 - 704
Abstract
Velo is a learning experience that combines robotics and simulation to help learners understand and apply a simple yet powerful programming model inspired by Braitenberg vehicles. In this model, programs are constructed only by making connections between sensors and actuators. Despite this simplicity, it is possible to achieve complex behaviors similar to that of animals. Velo is designed to be used in a curriculum that aims to help learners not only learn this programming model, but also the process of analyzing an existing (animal) behavior and breaking it down into a form useful for programming.
References
[1]
Valentino Braitenberg. 1986. Vehicles: Experiments in synthetic psychology. MIT press.
[2]
Po-Yao Chao. 2016. Exploring students’ computational practice, design and performance of problem-solving through a visual programming environment. Computers & Education 95 (2016), 202–215. https://doi.org/10.1016/j.compedu.2016.01.010
[3]
Neil Fraser. 2015. Ten things we’ve learned from Blockly. In 2015 IEEE Blocks and Beyond Workshop (Blocks and Beyond). 49–50. https://doi.org/10.1109/BLOCKS.2015.7369000
[4]
Michael S. Horn, Jeremy Baker, and Uri J. Wilensky. 2020. NetTango Web. https://netlogoweb.org/nettango-builder
[5]
Michael S. Horn, Corey Brady, Arthur Hjorth, Aditi Wagh, and Uri Wilensky. 2014. Frog Pond: A Codefirst Learning Environment on Evolution and Natural Selection. In Proceedings of the 2014 Conference on Interaction Design and Children (Aarhus, Denmark) (IDC ’14). Association for Computing Machinery, New York, NY, USA, 357–360. https://doi.org/10.1145/2593968.2610491
[6]
Stephen R. Kellert. 1985. Attitudes toward Animals: Age-Related Development among Children. The Journal of Environmental Education 16, 3 (1985), 29–39. https://doi.org/10.1080/00958964.1985.9942709 arXiv:https://doi.org/10.1080/00958964.1985.9942709
[7]
D Mioduser, ST Levy, and V Talis. 2002. Kindergarten children’s perception of robotic-control rules. In Intl Conf Learning Sciences.
[8]
Izabel C Olson and Michael S Horn. 2011. Modeling on the table: agent-based modeling in elementary school with NetTango. In Proceedings of the 10th International Conference on Interaction Design and Children. 189–192.
[9]
Seymour Papert and Idit Harel. 1990. Situating constructionism. (1990).
[10]
Mitchel Resnick, John Maloney, Andrés Monroy-Hernández, Natalie Rusk, Evelyn Eastmond, Karen Brennan, Amon Millner, Eric Rosenbaum, Jay Silver, Brian Silverman, 2009. Scratch: programming for all. Commun. ACM 52, 11 (2009), 60–67.
[11]
Eric Schweikardt and Mark D Gross. 2008. Learning about complexity with modular robots. In 2008 Second IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning. IEEE, 116–123.
[12]
Arnan Sipitakiat, Paulo Blikstein, and David P Cavallo. 2004. GoGo board: augmenting programmable bricks for economically challenged audiences. (2004).
[13]
José-Manuel Sáez-López, Marcos Román-González, and Esteban Vázquez-Cano. 2016. Visual programming languages integrated across the curriculum in elementary school: A two year case study using “Scratch” in five schools. Computers & Education 97 (2016), 129–141. https://doi.org/10.1016/j.compedu.2016.03.003
[14]
Seth Tisue and Uri Wilensky. 2004. NetLogo: Design and implementation of a multi-agent modeling environment. In Proceedings of the Agent, Vol. 2004. Springer Cham, Switzerland, 7–9.
[15]
Sokratis Tselegkaridis and Theodosios Sapounidis. 2021. Simulators in educational robotics: A review. Education Sciences 11, 1 (2021), 11.
[16]
Uri Wilensky and Seymour Papert. 2010. Restructurations: Reformulations of knowledge disciplines through new representational forms. Constructionism 17 (2010), 1–15.
[17]
Michelle Hoda. Wilkerson-Jerde. 2012. The DeltaTick Project: Learning Quantitative Change in Complex Systems with Expressive Technologies.
Index Terms
- Velo: Exploring Animal Behavior Modeling through Hybrid Robotics-Simulation Learning Experience
Recommendations
Stability of complex spike timing-dependent plasticity in cerebellar learning
AbstractDynamics of spike-timing dependent synaptic plasticity are analyzed for excitatory and inhibitory synapses onto cerebellar Purkinje cells. The purpose of this study is to place theoretical constraints on candidate synaptic learning rules that ...
From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation
Synaptic plasticity is a major mechanism for adaptation, learning, and memory. Yet current models struggle to link local synaptic changes to the acquisition of behaviors. The aim of this paper is to demonstrate a computational relationship between local ...
Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells
Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus ...
Comments
Information & Contributors
Information
Published In
June 2023
824 pages
ISBN:9798400701313
DOI:10.1145/3585088
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 19 June 2023
Check for updates
Author Tags
Qualifiers
- Extended-abstract
- Research
- Refereed limited
Conference
IDC '23
Sponsor:
Acceptance Rates
Overall Acceptance Rate 172 of 578 submissions, 30%
Upcoming Conference
IDC '25
- Sponsor:
- sigchi
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 82Total Downloads
- Downloads (Last 12 months)19
- Downloads (Last 6 weeks)4
Reflects downloads up to 25 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format