As mentioned in the Round-2 announcement for Multi-Agent Behavior Challenge participants who make a submission in round-2 can win up to $400 AWS credits.
Keep reading to see how you can claim AWS credits for yourself or for your team
Eligibility
You (or your team) must have received scores higher than the below-mentioned scores in any of the 2 tasks.
On the Ant & Beetle Video Data task,you must beat a mean F1 score of 0.606. Here’s the baseline for the Ant & Beetle Task, which achieves a mean F1 score of 0.591.
On the Mouse Triplet Video Data task, you must beat a mean F1 score of 0.306. Here’s the baseline for the Mouse Triplet Task, which achieves a mean F1 score of 0.292.
Each participant (or team) can claim a $200 credit code for each target beaten (up to $400 total.)
Please note:
We will be sharing 50 X $200 = $10,000 worth of AWS Credits. The distribution will happen on a first come first serve basis and will cease once all the 50 codes (each for $200) are distributed.
For teams claiming the code, please nominate one person to represent. The code will be mailed to that team member.
How to redeem?
Please share the following as a reply to this thread to receive your code.
Team name (if relevant):
Submission id (the one that beats baseline as defined above):
How much did you improve over the relevant baseline score?:
A brief intro about you (Us and the participants would love to know what brought you to this challenge):
We will be sending out the AWS credits every week after verifying the details. After receiving your code, you can go to this website and claim your credits.
If you haven’t gone through the baselines, check them out here
For mouse triplet:
Submission id: 184298
How much did you improve over the relevant baseline score?: 0.217 → 0.258
A brief intro about you: I have a bit of spare time before I start full time work after finishing studying
Submission id (the one that beats baseline as defined above): #186391
How much did you improve over the relevant baseline score?: 0.557 → 0.568
A brief intro about you (Us and the participants would love to know what brought you to this challenge): A Ph.D. student in Causal Multi-agent Systems
Submission id (the one that beats baseline as defined above): 179765
How much did you improve over the relevant baseline score?: avg rank - 7.920 to 5.310
A brief intro about you (Us and the participants would love to know what brought you to this challenge): I like to work simultaneously on fundamental R&D in terms of systems (along with data crunching to terminal solution) including Neural Network Architectures (on every domain, i.e. CV, NLP, TSA and so on), Neuro-Dynamic Programming, Cellular Automaton & Swarm Intelligence (long term).