Takayuki Ito Laboratory 2013

 

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Takayuki Ito Laboratory 2013

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pages scoring rule in electricity pricing 2 3 4 5 6 7 8 10 9 group formation based on linguistic mediation rules 11 12 13 14 15 16 17 18 19 20 openstreetmap 21 23 24 25 26 22 k-implementation 2011-2012 1

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collective intelligence harnessgooglewikipedia phev phev phev 1,000 10,000 lrt a 2

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scoring rule in electricity pricing member shantanu chakraborty 1.introduction in this article a scoring rule based mechanism is proposed for consumers in order to determine the day ahead time dependent pricing the consumers will be rewarded a discount on the price to measure up how well they predict the shifting the devices/loads towards the lower demand lower price as well periods a control feedback loop is created between energt provider and consumers using the time-dependent pricing the reward mechanism is based on a strictly proper scoring rule the scoring rule is chosen to reflect to work with continuous variable the normal distribution as in the proposed method and measure up how accurate the prediction could be the continuous ranked probability score possess such characteristics 3 continuous ranked probability score in order to rightfully incentive the consumers on their prediction of device shifting the continuous ranked probability score crps is applied crps is a strictly proper scoring rule which is used for continuous variable since the traditional forms of proper and strictly proper and scoring rules are usually not work with continuous variables in the proposed method gaussian distribution is used to model the consumers device shifting prediction and associated confidence again crps s ability to assess the participating agents consumers in this model regarding prediction closeness also a reason to choose it as the scoring mechanism in this model 4.result and summary 2 system model this model considers a day-ahead pricing scheme in which providers publish their prices one day in advance with day-ahead pricing users can schedule their device usage for the upcoming day so as to optimize their amount spent and willingness to shift their device usage the provider s goal is to incentivize consumer in the right way so that they shift their energy consumption to periods of lower demand the right way is to provide rewards as a form of discount starting with a flat fee price range a scoring rule the of is applied to the correctly on their of amount incentivize truthfulness shifting consumers predicting based the proposed crps based pricing mechanism is tested on a part of ontario power system data this method can properly incentivizes the consumers to report their willingness of shifting devices properly into the lower demand/price period by providing them rewards in form of discount the simulation results shows that the method is able to reduce the hourly load demand for the consumers in a day ahead pricing scheme the qualitative result is agree with it since the method is also able to deduce 25 of the total price 4

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1 web 100 20 48 web 2 twitter twitter twitter 2 twitter 2 3 1 3 100 5

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ebay google np 6

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dasgupta maskin [dasgupta2000 contingent bids a efficient aamas2006 takayuki ito david parkes instantiating the contingent bids model of truthful interdependent value auctions in the proceedings of the fifth international joint conference on autonomous agents and multi-agent systems aamas2006 2006 best paper award florin constantin david parkes takayuki ito online truthful auctions for bidders with interdependent values in the proceedings of the sixth international joint conference on autonomous agents and multi-agent systems aamas2007 2007 poster david c parkes d-i 2007 david c parkes d-i 2007 7

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multi-issue negotiation 1 2 1 2 100 ga .discountfactor ga ga 8

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anac 1 2012 aamas2012 anac2 012anac anac 1genius 3 2 anac anac anac 1 1 anac 2.1 anac 4 anac2012 agentmr anac2012 anac2012 7 2.2 genius anac genius 2 genius anac genius 5 anac anac2012 anac2013 9

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group formation based on linguistic mediation rules members rafik hadfi and takayuki ito 1.introduction in this paper we propose a way to group agents through a set of metrics used to compare the agents constraints utilities as well as the certainties over their possible outcomes to put this straightforward we assume that our model is based on the following assumptions in real life we believe that people who have similar beliefs certainties relative to a specific situation as well as the same preferences utilities over the same common outcomes could reach a system is composed of two levels an upper level related to the mediator or the consensus level and a level related to the agents where the distributed hierarchical clustering will be executed based on the decisional metric once the clustering is done a function f will be generated and will help in submitting the dsvs to the mediator reasonable agreement more optimally and smoothly than if they had different certainties or preferences over different outcomes precisely we define a decision structure value dsv which gives a reasonable condition under which agents having similar decision structures can form a group therefore formed groups will benefit from the cooperation of its members by satisfying their constraints as well as maximizing their payoffs under such criterion the mediator will perform a clustering of the structural values to form groups and then use a linguistically expressed weighted mediation averaging rule based on ordered that operators owa as in the figure 1 the architecture of the 3 results and conclusion we proposed the notion of decisional structure value as a main criterion for agents decisional settings comparison the defined structure-value captures the main similarities between the agents decisional settings we have shown that it is possible to represent such decisional setting as a constraints utilities belief space furthermore we provided a distributed group formation framework that constructs a decisional structure value function through a hierarchical clustering of the agents this function will be used by the mediator additionally to the mediation rules to form the groups formalize the consensus policy experiments have been performed to test the existence of the decision structure value as well as its capability to describe an agent s decision structure moreover the decision structure value was used for a distributed hierarchical clustering of the agents 2 system architecture 10

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it cookpad ,2030 90 140 1 web 1 11

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kddi 1 2 3 3 kddi kddi 12

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deyue deng 1 ,sns ,sns 3.svm support vector machinesvm 2 10 10 paul graham gray robinson 2 svm 3 svm 95 1 gray robinson 4 95 3 2 5 13

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