The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/19175684

Tim Baarslag (2022): Results from the Automated Negotiating Agents Competition (ANAC 2020). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19175684.v1

Dataset

• Artificial Intelligence and Image Processing

ANAC, Artificial Intelligence (AI), Automated negotiation, Autonomous agents, Multi-agent systems (MAS)

CC BY 4.0

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by Tim Baarslag

The Automated Negotiating Agent Competition (ANAC) is an international tournament that has been running since 2010 to bring together researchers from the negotiation community.In 2020, ANAC had five different negotiation research challenges:

• Agent Negotiation and Elicitation (GeniusWeb framework)
• Human-Agent Negotiation (IAGO framework)
• Werewolf Game (AIWolf Framework)
• Supply Chain Management (NegMas framework)
• HUMAINE (HUman Multi-Agent Immersive NEgotiation)

This dataset contains the results from the Automated Negotiating Agents Competition 2020, including the domains used in the tournament and overall individual utility calculations.

• 2022-02-16 first online, published, posted

4TU.ResearchData

.zip

• Representing Users in a Negotiation (RUN): An Autonomous Negotiator Under Preference Uncertainty (grant code 639.021.751) [more info...] Dutch Research Council

Centrum Wiskunde & Informatica, Utrecht University