TY - DATA
T1 - Results from the Automated Negotiating Agents Competition (ANAC 2020)
PY - 2022/02/16
AU - Tim Baarslag
UR - https://data.4tu.nl/articles/dataset/Results_from_the_Automated_Negotiating_Agents_Competition_ANAC_2020_/19175684/1
DO - 10.4121/19175684.v1
KW - Autonomous agents
KW - Multi-agent systems (MAS)
KW - Artificial Intelligence (AI)
KW - Automated negotiation
KW - ANAC
N2 - 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:
			<ul><li>Agent Negotiation and Elicitation (<a href="https://ii.tudelft.nl/GeniusWeb/">GeniusWeb framework</a>)</li><li>Human-Agent Negotiation (<a href="https://myiago.com">IAGO framework)</a></li><li>Werewolf Game (<a href="http://aiwolf.org/en/">AIWolf Framework</a>)</li><li>Supply Chain Management (<a href="http://www.yasserm.com/negmas/">NegMas framework</a>)</li><li>HUMAINE (<a href="https://cisl.rpi.edu/humaine2020">HUman Multi-Agent Immersive NEgotiation</a>)</li></ul>This dataset contains the results from the Automated Negotiating Agents 
Competition 2020, including the domains used in the tournament and overall individual utility 
calculations.
ER -