AgentSim: June Update (and Launch!)


AgentSim Launch

My goal has been to develop a platform that allows anyone to develop and test their algorithms for multi-agent systems. My original goals are here, and my April update here.

Since April, I have been working to get this project to a stage where people can start using it. Now, after completing the API, DSL, visualization, and sample algorithms, it is time for the launch of AgentSim!    

If you are interested in trying it out, email me at aditshah00@gmail.com, and I would really appreciate any feedback! I am willing to expand the functionality and algorithms available on this platform.

For an overview of the rationale, code, and visualization of my project, check out this presentation and demo!

Components

There are four main components to this project:
  • Node API
    • A Java and Kotlin API for creating and manipulating each node/agent
    • Uses gRPC in the background to emulate broadcast messages of information updates (including location and weights) 
  • DSL (Domain-specific language)
    • An intuitive way to create algorithms using the Node API
  • Visualization
    • Users can visually see how their algorithms perform in a 2-dimensional grid-based environment
  • Sample Algorithms
    • So far, I have implemented a Greedy and Log-Linear Learning algorithm with the AgentSim DSL, which are described in my research paper from UC Santa Barbara here.

Progress Update

Accomplishments in May/June

  • Completed the DSL (domain specific language) for defining algorithms on top of the core Java/Kotlin API
  • Implemented the Greedy Algorithm and Log-Linear Learning algorithm
  • Developed a visualization
    • Used p5.js (Processing library for Javascript) to create the visualization
    • Runs on a web server made by Ktor in Kotlin
  • Refactored and reorganized all code for usability
  • Commented and documented all code: detailed docs can be found on the main GitHub page readme: https://github.com/ashah03/kotlin-distributed-framework

Future Tasks

  • Begin gathering user feedback
  • Implementing new platform features and sample algorithms based on feedback
  • Create algorithm analytics functionality: computation time, convergence time, etc.

    Comments

    Post a Comment

    Popular posts from this blog

    AgentSim: Rationale and Goals

    I am spending the five weeks of March Term and Spring Break working on this, with plans to continue this project in the summer. For the overall project, I have two core goals: 1) Develop a self-contained framework necessary to simulate and test the efficacy of algorithms for a multi-agent system (e.g. drones, ground robots) , with an easy-to-use and documented API with cross-language support. 2) Develop, implement, and test algorithms with a specific application in mind. Identify other possible applications of such a system.  The idea for this project began with the research I conducted at the University of California, Santa Barbara in the summer of 2019. I focused on simulating a system where a set of distributed drones have to maximize their combine coverage in a weighted environment, but in such a way where each drone makes its own decisions. There is no centralized server or node providing instructions to all other drones. The drones also have limited prior know...
    Read more

    Teaching Python at STEAM Series

    On Saturday, I taught my first programming class ever, at a STEAM workshop at Santa Clara University that was put on by WRRF. I really enjoyed teaching others how to program in Python, and all of the students at the class were quite engaged. When I committed to teaching this class with less than a week's notice, I had no idea where to start with the curriculum. What would students with no prior experience in programming learn from just a 90 minute preview? After I consulted with Paul and realized that he had an array of ideas on what I could teach, I brought him on board to help me teach the curriculum. I also invited Donovan to co-teach the class with me. After the three of us had our first discussion, I realized that there was no way the students would emerge from the class being Python experts. A successful class would mean that they would have a basic knowledge of Python fundamentals. The students would have enough knowledge of Python, and enough motivation, to continue le...
    Read more

    Positronics – Day 1

    Today was my first day at Positronics, a robotics software company, and I will be working here for the next three and a half weeks for our school's inaugural March Term. The System My goal is to optimize a robotics manufacturing process that Positronics has developed. The system assembles a heating plate for a vacuum chamber that is used for semiconductor manufacturing in a clean room environment. The system consists of a 6-axis  Universal Robot Arm , which has two attachments:  Robotiq  gripper, used for handling bolts, and a screwdriver (allen key). In order to assemble the vacuum plate, these are the steps the system must take: Attach the gripper attachment to the robot arm Pick up the bolts from a bolt holder and place them in each of the 40 holes on the plate Screw all bolts to the following torque settings: 5 lb-in 20 lb-in 40 lb-in 60 lb-in Verify the 60 lb-in of torque twice Optimization The system is already in deployment, but is in need of...
    Read more