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Abstract-Multi-issue negotiations are a central component of many important coordination challenges. Almost all previous work in this area has assumed that negotiation issues are independent, making it relatively easy to find high-quality agreements. In many real-world problem domains, however, issues are interdependent, making hard to find good agreement due to the nonlinearity of the agent's utility functions. The key challenge, in this context, is finding high-quality agreements without making unrealistic demands concerning how much agents reveal about their utilities. In this paper, we propose a protocol wherein the negotiating agents, working with the mediator, progress through a multi-phase narrowing of the space of possible agreements. We show that our method outperforms existing methods in large nonlinear utility spaces, and is computationally feasible for negotiations with as many as ten agents.

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We consider the problem of dynamic reconfiguration of robot teams when they encounter obstacles while navigating in formation, in an initially unknown environment. We have used a framework from coalition game theory called weighted voting games to analyse this problem and proposed two heuristics that can appropriately partition a robot team into sub-teams. We have experimentally verified our technique on teams of e-puck robots of different sizes and with different obstacle geometries, both on the Webots simulator and on physical robots. We have also shown that our technique performs faster and generates considerably fewer partitions than an existing robot coalition formation algorithm.

This paper examines the problem of distributed coverage of an initially unknown environment using a multi-robot system. Specifically, focus is on a coverage technique for coordinating teams of multiple mobile robots that are deployed and maintained in a certain formation while covering the environment. The technique is analyzed theoretically and experimentally to verify its operation and performance within the Webots robot simulator, as well as on physical robots. Experimental results show that the described coverage technique with robot teams moving in formation can perform comparably with a technique where the robots move individually while covering the environment. The authors also quantify the effect of various parameters of the system, such as the size of the robot teams, the presence of localization, and wheel slip noise, as well as environment related features like the size of the environment and the presence of obstacles and walls on the performance of the area coverage operation.

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We consider the problem of distributed coverage of an initially unknown environment using a multi-robot system. We specifically focus on a coverage technique for coordinating teams of multiple mobile robots that are deployed and maintained in a certain formation while covering the environment. We have analyzed our technique theoretically and experimentally to verify its operation and performance within the Webots robot simulator as well as on physical robots. Our experimental results show that our coverage technique with robot teams moving in formation can perform comparably with a technique where the robots move individually while covering the environment. We also quantify the effect of various parameters of the system such as the size of the robot teams, the presence of localization and wheel slip noise, as well as environment related features like the size of the environment and the presence of obstacles and walls on the performance of the area coverage operation.