1. A BDI-Based Capture The Flag Competition Using pyGOMAS
Contact email: firstname.lastname@example.org
Description: PyGOMAS (Python Game Oriented Multi-Agent System) is a framework for developing and simulating multi-agent systems (MAS) in a game-like environment. The pyGOMAS Multi-Agent Strategy Competition, leveraging this framework, invites teams to program AI agents for strategic challenges within a virtual battlefield. In the competition, the teams’ agents will demonstrate their capabilities in performing tasks like flag capture or defense. Adhering to strict rules for fair play and agent autonomy, this event not only tests AI strategy and teamwork but also promotes innovation and learning in the field of MAS.
Call for contributions: https://pygomas.webs.upv.es/index.php/submission/
2. The 15th Automated Negotiating Agents Competition (ANAC 2024)
Contact email: email@example.com
Description: The Automated Negotiating Agent Competition (ANAC) is an international tournament that has been running since 2010 to bring together researchers from the negotiation community. ANAC provides a unique benchmark for evaluating practical negotiation strategies in multi-issue domains and has the following aims: – to provide an incentive for the development of effective and efficient negotiation protocols and strategies for bidding, accepting and opponent modelling for different negotiation scenarios; – to collect and develop a benchmark of negotiation scenarios, protocols and strategies; – to develop a common set of tools and criteria for the evaluation and exploration of new protocols and new strategies against benchmark scenarios, protocols and strategies; – to set the research agenda for automated negotiation.
The previous competitions have spawned novel research in AI in the field of autonomous agent design which are available to the wider research community. This year, we introduce a variety of negotiation research challenges: – Automated Negotiation with Private Reservation Values (NegMas framework) – Supply Chain Management (NegMas framework)
Call for contributions: https://web.tuat.ac.jp/~katfuji/ANAC2024/#leagues
3. Computational Economics Competition
Contact email: firstname.lastname@example.org
Description: The macroeconomic taxation policy and micro-level individual savings and labor strategies have long been focal points of research in the field of economics. This entails dynamic interactions between the government and numerous micro-agents such as households, making it a prime candidate for exploration through AI methodologies. This issue includes two parallel tracks: solving optimal taxation for the government side and optimal savings and labor strategies for the household side. To encourage the development of AI in solving complex economic problems, we plan to host the 2nd Computational Economics Competition. This competition aims to encourage innovative approaches to addressing these complex economic issues and promises to provide fresh insights into the field.
Call for contributions: http://jidiai.cn/aamas_tax_2024/
4. Imperfect-information Card Games Competition
Contact email: email@example.com
Description:Texas Hold’em, Bridge and Mahjong are three popular strategic board games worldwide. Each game has plenty of advanced players, let alone the amateurs. These games often have complex game rules with enormously large state space, making designing a strong AI player challenging. In 2023, the online agent evaluation platform, Jidi, held the first Imperfect-information Card Games Competition and has attracted a large number of participants. Building on this momentum and in a dedicated effort to advance research in turn-based card game AI, we propose the second Imperfect-information Card Games Competition.
Call for contributions: http://jidiai.cn/aamas_2024/
5. Drone Routing Problems Challenge
Contact email: firstname.lastname@example.org
Description:The Drone Routing Problems (DRP) represent a cutting-edge challenge at the intersection of logistics, computer science, and operations research. This dynamic field has garnered substantial interest due to its potential for revolutionizing the logistics and delivery sectors. In this proposal, we consider a multiple drone delivery scenario, where the objective is to locate a set of collision-free optimal paths that further optimize a team goal. At the heart of DRP lies the goal of optimizing routes for a fleet of drones to ensure efficient, timely, and cost-effective delivery of goods.
Call for contributions: http://drp-challenge.com/#/rules-and-guidelines
6. International Intention Progression Competition
Description:A key problem for an agent with multiple, possibly inconsistent, goals is: `what should I do next’? What to do next can be formalised as the Intention Progression Problem (IPP): what means (course of action) to use to achieve a given (sub)goal, and which course of action (intention) to progress at the current moment. The objective of the International Intention Progression Competition is to incentivise and facilitate research around the multi-faceted problem of intention progression. Participants need to implement an agent/solver that will interact with a server and decide which intention to do next.
Call for contributions: https://www.intentionprogression.org/call-for-participants/
7. The Hybrid Intelligence Competition (HI Comp)
Contact email: email@example.com
Description:Hybrid Intelligence (HI) is an emerging system design paradigm in which artificial intelligence (AI) augments, as opposed to replacing, human intelligence. Although there is an increasing emphasis on the idea of HI in the AI literature, there is a lack of systematic methods and metrics for developing HI systems. The Hybrid Intelligence Competition (HI Comp) series aims to support the development of high-quality HI (Human-AI) teams, by exploring the possible benefits, risks, and consequences of collaboration between humans and AI systems. HI Comp aims at pushing the state-of-the-art in Human-AI collaboration and teaming, and at generating a first repository of scenarios for researchers and practitioners to guide the development and evaluation of HI teams. By delving into an interdisciplinary subject, and by minimizing the prerequisite technical expertise for participation, HI Comp invites participation from all segments of the AAMAS community.
Call for contributions: https://hybrid-intelligence-competition.github.io/HI-Comp-2024-AAMAS/
8. Maritime Capture-the-Flag (MCTF) Competition
Contact email: firstname.lastname@example.org
Description:The Maritime Capture the Flag (MCTF) Competition addresses the problem of multi-agent reinforcement learning (MARL) for playing a multi-player Capture-the-Flag game within a real-time simulation of a maritime gaming environment. Participants are required to submit software code in Python for three agents that can play the game as a team against an opponent team, while maximizing their team’s score. Example code for training agents to play MCTF using RLlib is included in the code repository that is provided. Capture the Flag is a commonly-played team-game involving two opposing teams playing within a bounded playing field. The field is divided into two halves, one for each team; each team has a flag located inside their respective half. The objective of each team is to score points by capturing the opponent’s’ flag, while not accruing negative points by preventing its own flag from being captured by the opponent’s team. The game ends after a certain, pre-determined duration. In this challenge, we consider a Maritime Capture-the-Flag (MCTF) game where the players are autonomous marine vehicles.
Call for contributions: https://sites.google.com/view/mctf2024/submit-your-entry