The project develops automated methods for the tool-aided design and analysis of multi-agent systems with incentives. These systems are natural models for real-world situations in which collections of actors interact with one another in an autonomous and self-interested manner. For example, such a system can model a set of software agents that participate in an internet-based protocol, such as an advertisement auction or crypto currency; a collection of robots that share physical or digital infrastructure; or a set of cells that participate in an evolutionary process. The project combines game-theoretic and logical methods to develop techniques for formal modeling, analysis, verification, and synthesis of such systems. The end objectives of the project include reliable engineering of protocols that govern interactions among autonomous agents, and computer-aided understanding of naturally occurring game-theoretic interactions.

The technical approach of the project has three dimensions. The first is the development of new formal models, correctness requirements, and abstraction and reasoning principles for multi-agent systems with incentives. Research directions include richer notions of equilibria in multi-agent systems, and effects of interaction and randomization on equilibria. Second, the project studies algorithmic tools for analysis and verification of multi-agent systems with incentives with respect to desired requirements regarding system behaviors and equilibria. The third direction is to automatically synthesize mechanisms so as to guarantee desired properties. Applications from a range of areas, including financial protocols, robotics, and biology, are used to guide and evaluate the research.

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Rice University
United States
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