Alexander Babanov

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This paper investigates methods of reducing risk in market-based auctions of tasks with complex time constraints and interdependencies. The research addresses problems in a contracting setting in which a buyer has a set of tasks to be performed. Because of the complex dependencies among the tasks, a task not completed on time might have devastating effect(More)
In related research we have proposed a market architecture for multi-agent contracting and we have implemented prototypes of both the market architecture and the agents in a system called MAGNET. A customer agent in MAGNET solicits bids for the execution of multi-step plans, in which tasks have precedence and time constraints, by posting a Request for(More)
In our previous research we suggested an approach to maximizing agents preferences over schedules of multiple tasks with temporal and precedence constraints. The proposed approach is based on Expected Utility Theory. In this paper we address two mutually dependent questions: (a) what are the properties of the problem domain that can facilitate efficient(More)
In previous work we proposed an approach for computing an agentýs preferences over different schedules of tasks, and for soliciting desirable bid combinations to cover the tasks. The proposed approach finds schedules that maximize the agentýs Expected Utility. The maximization problem is hard because the domain is piece-wise continuous, with the(More)
We present an auction-based approach to allocate tasks that have complex time constraints and interdependen-cies to a group of cooperative agents. The approach combines the advantages of planning and scheduling with the ability to make distributed decisions. We focus on methods for modeling and evaluating the decisions an agent must make when deciding how(More)
We propose an evolutionary framework for studying agents that interact in electronic marketplaces and describe how to use the framework to study the dynamics of interaction and evolution of agent strategies. We present experimental results from a simulated market, where service providers compete for customers using multiple strategies. The results show how(More)
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