What we’re about
Hands-on project-oriented data science, with a heavy focus on machine learning and artificial intelligence. We're here to get neck-deep into projects and actually do awesome things!
Join our new discord https://discord.gg/xtFVsSZuPG where you can:
- discuss more AI/ML papers
- suggest/plan events
- share and discuss github projects
- find and post jobs on our jobs channel
- buy/sell used local gpu/server equipment
- scroll our social media aggregators for the latest AI research news across Bsky, X, Reddit, Youtube, Podcasts, and more
The meetup consists of:
- recurring study groups (if you want to start one, just notify Ben to be made a meetup co-organizer).
- intermediate/advanced working groups (starting in 2019)
- occasional talks and gathering (aiming for at least quarterly starting in 2019)
Upcoming events
9
•OnlineMulti-Agent Reinforcement Learning: Chapter 4 Solution Concepts for Games
OnlineThis meeting will cover material from Chapter 4 of Multi-Agent Reinforcement Learning: Foundations and Modern Approaches. We will cover normal form games and types of solutions that exist such as minimax and Nash equilibrium. Initially we will consider two player zero sum games with only two actions and slowly expand the complexity of the reward function and dimensionality. For many game types, the equilibrium solutions are not unique, so the challenge becomes selecting which one is relevant to us and how to calculate it.
As usual you can find below links to the textbook, previous chapter notes, slides, and recordings of some of the previous meetings.
Meetup Links:
Recordings of Previous RL Meetings
Recordings of Previous MARL Meetings
Short RL Tutorials
My exercise solutions and chapter notes
Kickoff Slides which contain other links
MARL Kickoff SlidesMARL Links:
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
MARL Summer Course Videos
MARL SlidesSutton and Barto Links:
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Video lectures from a similar course12 attendees- •Online
Reinforcement Learning: Topic TBA
OnlineTypically covers material from the following textbook: Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
As usual you can find below links to the textbook, previous chapter notes, slides, and recordings of some of the previous meetings.
Meetup Links:
Recordings of Previous Meetings
Short RL Tutorials
My exercise solutions and chapter notes
Kickoff Slides which contain other links
MARL Kickoff SlidesMARL Links:
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
MARL Summer Course Videos
MARL SlidesSutton and Barto Links:
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Video lectures from a similar course6 attendees - •Online
Reinforcement Learning: Topic TBA
OnlineTypically covers material from the following textbook: Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
As usual you can find below links to the textbook, previous chapter notes, slides, and recordings of some of the previous meetings.
Meetup Links:
Recordings of Previous Meetings
Short RL Tutorials
My exercise solutions and chapter notes
Kickoff Slides which contain other links
MARL Kickoff SlidesMARL Links:
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
MARL Summer Course Videos
MARL SlidesSutton and Barto Links:
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Video lectures from a similar course4 attendees - •Online
Reinforcement Learning: Topic TBA
OnlineTypically covers material from the following textbook: Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
As usual you can find below links to the textbook, previous chapter notes, slides, and recordings of some of the previous meetings.
Meetup Links:
Recordings of Previous Meetings
Short RL Tutorials
My exercise solutions and chapter notes
Kickoff Slides which contain other links
MARL Kickoff SlidesMARL Links:
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
MARL Summer Course Videos
MARL SlidesSutton and Barto Links:
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Video lectures from a similar course4 attendees
Past events
654
Group links
Organizers
Members
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