ANAC2013 The Fourth International Automated Negotiating Agents Competition

To be held in conjunction with the Nineth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2013), Saint Paul, Minnesota, USA, 6th-10th May 2013.

Participants do not need any pre-registration


15 Jan 2013
Agent registration site open! ==> Agent Upload

In the old registration site, a participant needed preregistration. But in the current registration site, participants do not need any pre-registration. Please register your agent and domain with your information directly.

Call for Participation

We would like to invite you to participate in the fourth Automated Negotiating Agents Competition (ANAC). This competition brings together researchers from the negotiation community and provides a unique benchmark for evaluating practical negotiation strategies in multi-issue domains. The three previous competitions have spawned novel research in AI in the field of autonomous agent design which are available to the wider research community. The focus of this year’s competition is interleaving learning with negotiation strategies. (see “Changes in Rules"). The declared goals of the competition are

  1. to encourage the design of practical negotiation agents that can proficiently negotiate against unknown opponents and in a variety of circumstances,
  2. to provide a benchmark for objectively evaluating different negotiation strategies,
  3. to explore different learning and adaptation strategies and opponent models, and
  4. to collect state-of-the-art negotiating agents and negotiation scenarios, and making them available to the wider research community.


The aim for the entrants to the competition is to develop an autonomous negotiation agent as well as submit a negotiation scenario. Performance of the agents will then be evaluated in a tournament setting, where each agent is matched with all other submitted agents, and each pair of agents will negotiate in each submitted negotiation scenario. Negotiations are repeated several times to obtain statistically significant results. The winning agent will be the one with the highest overall score.

A negotiation scenario consists of a specification of the objectives and issues to be resolved by means of negotiation. This includes the preferences of both negotiating parties about the possible agreements. The preferences of a party are modelled using linearly additive, multi-issue utility functions.

Rules of Encounter

Negotiations are bilateral and based on the alternating-offers protocol. Offers are exchanged in real time with a deadline after 3 minutes. This means that the number of offers exchanged within a certain time period varies and depends on the computation required by the agents. If no agreement is reached by the deadline, or if either agent chooses to terminate the negotiation before the deadline, both agents receive their utility of conflict. In addition, there will be a discount factor in about half of the domains, where the value of an agreement decreases over time. The challenge for an agent is to negotiate without any knowledge of the opponent's preferences and strategy. Although each agent participates in many negotiation sessions, against different opponents, and in a wide variety of negotiation scenarios, agents cannot learn between negotiations. This means that negotiation agents only have the opportunity to adapt and learn from the offers they receive within a single negotiation session.

Changes with respect to ANAC 2012

Focus for 2013: Learning and Adaptation

This year we allow agents to save and load data from past negotiation sessions (with some constraints that are specified in the javadoc). Agents may use this information to learn about and adapt to domains over time, and to use this information to negotiate better with future opponents!


The negotiation tournament is run using the java-based GENIUS negotiation platform, which has been developed to facilitate research in the area of bilateral multi-issue negotiation. GENIUS allows easy development and integration of existing negotiating agents. GENIUS can be used to simulate individual negotiation sessions as well as tournaments between negotiating agents in various negotiation scenarios. The core functionality of the system includes:
(1) specification of negotiation domains and preference profiles;
(2) simulation of a bilateral negotiation between agents;
(3) analysis of the negotiation outcomes and negotiation dynamics. It furthermore allows the specification of negotiation domains and preference profiles by means of a graphical user interface.

The GENIUS platform, together with the agents and scenarios from the previous competitions are available for download. More information about the platform can be found at the GENIUS web page. The agents from last year's competition are included in this download. Their source code is also available for reference.

Qualifying Round and Finals

There will be initial qualifying rounds, and the top 8 performing agents will continue to the finals, which will be held at the AAMAS conference.

It is expected that teams that make it through to the finals will have a representative attending the AAMAS 2013 conference. Each team in the final will have the opportunity to give a brief presentation describing their agent.


The conference will be held at the Crowne Plaza, St. Paul, Minnesota, USA

Large Map - OpenStreetMap

Organising Committee

  • Prof. Dr. Takayuki Ito, Nagoya Institute of Technology
  • Prof. Dr. Catholijn Jonker, Delft University of Technology
  • Dr Kobi Gal, Ben-Gurion University
  • Prof. Dr. Sarit Kraus, University of Maryland and Bar-Ilan University
  • Dr. Koen Hindriks, Delft University of Technology
  • Dr. Raz Lin, Bar-Ilan University
  • Tim Baarslag, Delft University of Technology


prizes are $1500 in total.


For any questions, the main contact is Yogev Caspi (yogevk at