Combinatorial auction, one of most popular market mechanisms, is well-known mechanism for effective resource allocation to self-interested agents. In real scenarios, since the auction mechanism has to clear the market very frequently, actually there is not enough time to compute exact optimal winners. In this paper, we show that some approximation algorithms provide sufficient quality of winners for auctions that have large number of bids but have hard time constraints. Furthermore, we compare and discuss about desirable properties of such approximation algorithms to be embedded in application systems.
This work presents the design and prototyping of a protocol-aware and cognitively enhanced Robot agent. A set of protocols have been defined which support autonomous robot team mission activity. These include a Team Work Effort protocol and ancillary protocols which support situation awareness and assist the robot team in flexibly executing the mission. The Robot agents are engaged in a simulated Lunar-based Scientific Sampling Mission. We utilize the Distributed Control Framework (DCF) robotics software as the platform in which to develop the protocol-aware and cognitively enhanced Robot agent; the DCF platform offers a basic Robot agent construct. Selecting a particular robotics software framework is necessary in order to develop the design and perform prototyping. However, the conceptual approach and protocols may be utilized in other robotics software frameworks, provided they offer the notion of a communicative robot agent. Mission simulations utilizing the protocols and enhanced Robot agents were performed in both software and hardware. The hardware prototyping utilized the Amigo-bot platform.
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