Demos for some projects of SEN4
Automated Negotiation and Bundling of Information Goods
Demo of software which simulates negotiations between a seller who sells bundles of goods (or
services) to many customers. The seller bargains with each
customer individually. A negotiation concerns the selection
of a subset from a collection of goods, viz. the bundle,
together with a price for that bundle.
(This work is done in the context of the
ASTA
project.)
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Using Utility Graphs to Model Complex Multi-Issue Negotiations
This is a demonstration of an automated negotiation between a buyer and a seller agent over the composition of a bundle of goods with inter-dependent valuations (more specifically k-addtitive valuations).In this model, dependencies between different items in the utility function of the buyer are presented in the form of a utility graph.
(This work is done in the context of the
DEAL
project.)
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Bidding with decommitment in a multi-agent transportation model
This demo visualizes the operation of a Multi-Agent system where the agents optimize
the route followed by trucks transporting loads from pick-up points to depots.
The Agents ensure
that trucks are efficiently filled by bidding for new cargo in online auctions,
even as the truck is busy transporting loads.
Furthermore, we show that additional increase in profits can be realized by use
of decommitment. Decommitment is the action of foregoing of a contract for
another (superior) offer.
(This work is done in the context of the
DEAL
project.)
Note. It takes about
2 minutes for the simulation to run. Before that,
nothing interesting is
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shown on your screen. Meanwhile, you may open the java console in your
browser to verify that the simulation is still running!
Market-based Recommendation: Agents that Compete for Consumer Attention
This software aims to demonstrate the idea of Market-based Recommendation, where advertisers bid for the placement of an advert for a single encounter with a single customer. Given feedback from the customer and some information about the interest of the customer, the advertisers can learn to target only those customers that are likely to be interested in the advert.
(This work is done in the context of the
ASTA
project.)
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Decentralized reputation-based trust
XA visulization is shown of software where decentralized reputation-based trust is studied: there is no central
reputation storage, but agents are connected in a reputation network for
exchanging reputation information with their (reputation) neighbors.
They use this information together with their private experiences with
others, for building up and maintaining trust models about other agents,
which allow them to assess the accuracy of task related information
received from those other agents.
(This work is done in the context of the
CIM
project.)
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Decentralized Management of Intermediate Electricity Networks by Agents using Local Dynamic Pricing
With the increasing use of distributed power generation, the
management of electricity networks (electricity grids) is becoming
more and more complex. This impacts many important parameters of the
electricity network management, such as stability, peak loading,
efficiency, and potential excess cable deterioration. We demonstrate a
test-bed for the study of the effect of price-discrimination between
areas which are connected to a power network on power flows in that
network. We focus on the so-called intermediate-voltage networks. The
system gives extensive visual information on current flows between
areas and power demand and production in areas. The user can
interactively specify time-dependent production and consumption curves
and then run a simulation of the flows in the network. By
incorporating different pricing strategies and objectives one can
study the effect of the one on the other.
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A Clearing Market for Electricity.
A modelling framework which implements a clear-
ing market for electricity (CleMEl). It is is a deliverable in the action line
"Market models and user experience" within the EIT ICT Labs program.
The framework provides a fundamental building block to design economic
test cases and scenarios. In particular, it represents a market, which accepts
bids on electricity from both suppliers and consumers. Bids can
be designed in several linear or non-linear formats, using both continuous
and non-continuous functions. Intelligent bidding strategies can be
plugged into the process.
A demonstration with two smart appliances is shown as an example.
Note: In this demo-version, some menu-items are shown, but are disabled.
In particular, it is not possible to write generated data to file.
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