Coordination is of great significance to multiagent systems, and in recent years, there has been much fruitful achievement in this area, such as refinement of dependencies under some hypothesis, the dynamic selection of coordination mechanisms, new coordination models using swarm intelligence, new methods using varied techniques like case based reasoning, reinforcement learning, distributed log...

This paper considers a dynamic variant of a coordination problem that was studied in, e.g., [9, 7, 8]. The original problem is concerned with a static task environment where all composite tasks consisting of elementary tasks and their interdependencies are given in advance. We introduce a dynamic variant of this problem where multiple composite tasks arrive dynamically in the system. We present...

In this paper we study the problem of parameterized assignment. This problem arises when a team of mobile robots must decide what role to take on in a given planar formation, where the parameters are the rotation and translation of the formation. A suite of suboptimal, but computationally tractable (polynomial time) algorithms are given, based on a solution to the problem of finding the optimal...

We propose the term Coordination Support to denote the services offered by the infrastructure used to deploy MultiAgent Systems (MAS). In fact, these services provide a means to enact the coordination model defined in MAS design. We detail Coordination Support’s functionalities and group them into different layers. Furthermore we extend them and propose an additional Assistance layer devoted to...

Reasoning about Action and Change (RAC) and Answer Set Programming (ASP) are two well-known fields in AI for logic-based reasoning. Each paradigm bears unique features and a possible integration can lead to more effective ways to address hard AI problems. In this paper, we report on implementations that embed RAC formalisms and concepts in ASP and present the experimental results obtained, buil...

Team coordination of non-player characters can create a deeper sense of immersion in real-time games by allowing characters to work together to produce better tactics and strategy. Achieving multi-agent coordination can be a difficult problem, and can incur substantial computational costs. Our goal with this work is to produce a reactive method for coordinating game characters that will allow c...

Learning agents increase their team’s performance by learning to coordinate better with their teammates, and we are interested in forming teams that contain such learning agents. In particular, we consider finite training instances for learning agents to improve their coordination before the final team is formed. We formally define the learning agents team formation problem, and focus on learni...

Distributed information systems for decision-support, logistics, and e-commerce involve coordination of autonomous information resources and clients according to specific domain independent and domain dependent policies. A major challenge is handling dynamic changes in the priorities, preferences, and constraints of the clients and/or the resources. Addressing such a challenge requires solution...

Modern distributed systems tend to be conglomerates of heterogeneous subsystems, which have been designed separately, by different people, with little, if any, knowledge of each other. A single agent operating within a hybrid system of this kind may have to coordinate its activities with members of several such subsystems, under different coordination policies. To support coordination in such h...

Similarly to human organizations, where the environment plays a fundamental role in supporting social activities, the environment of a multi-agent system (MAS) is the natural place where understanding and designing agent coordination. Accordingly, we propose the notion of coordination artifact as a unifying abstraction for engineering environment-based coordination of agents. This is meant to c...