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Project description
This repository contains agents (negotiators) submitted to the ANL league of the ANAC Competition
To install this package just run:
pip install anl-agents
There are two ways to submit agents to this repository:
- Participate in the ANAC competition https://anac.cs.brown.edu/anl
- Submit a pull-request with your agent added to the contrib directory.
Getting lists of agents
You can get any specific subset of the agents in the library using get_agents()
. This function
has the following parameters:
- version: Either a competition year (2024, ...) or the value "contrib" for all other agents. You can also pass "all" or "any" to get all agents.
- track: The track (advantage, utility, welfare, nash, kalai, kalai-smorodinsky)
- qualified_only: If true, only agents that were submitted to SCML and ran in the qualifications round will be returned.
- finalists_only: If true, only agents that were submitted to SCML and passed qualifications will be returned.
- winners_only: If true, only winners of SCML (the given version) will be returned.
- top_only: Either a fraction of finalists or the top n finalists with highest scores in the finals of SCML.
- as_class: If true, the agent classes will be returned otherwise their full class names.
For example, to get the top 10% of the "advantage" track finalists in year 2024 as strings, you can use:
get_agents(version=2024, track="advantage", finalists_only=True, top_only=0.1, as_class=False)
Winners of the ANL 2024 Competition
Advantage Track
- First Place: Shochan
- Second Place: UOAgent
- Third Place: AgentRenting2024
You can get these agents after installing anl-agents by running:
get_agents(2024, track="advantage", winners_only=True)
Nash Track
- First Place: Shochan
You can get this agent after installing anl-agents by running:
get_agents(2024, track="nash", winners_only=True)
Installation Note
If you are on Apple M1, you will need to install tensorflow before installing this package on conda using the method described here
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