anl-agents 0.1.2

Agents submitted to the ANL league of ANAC 2025 since 2024

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:

1. Participate in the ANAC competition https://anac.cs.brown.edu/anl
2. 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 ANL and ran in the qualifications round will be returned.
• finalists_only: If true, only agents that were submitted to ANL and passed qualifications will be returned.
• winners_only: If true, only winners of ANL (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 ANL.
• 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 2025 Competition

• First Place (tie): RUFL
• First Place (tie): SacAgent
• Third Place: UfunAtAgent

You can get these agents after installing anl-agents by running:

get_agents(2025, winners_only=True)

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