• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 7,702
Next 10 →

Table II. The capacities of the buyers and sellers are

in Market power and efficiency in a computational electricity market with discriminatory double-auction pricing
by James Nicolaisen, Valentin Petrov, Leigh Tesfatsion 2001
Cited by 29

Table 1. Buyer seller interaction

in unknown title
by unknown authors
"... In PAGE 8: ... 3. Gain Vs Transaction for RL Buyer Table1 shows the number of purchases made by a buyer from each seller type. Table 1.... ..."

Table 3] in which the buyer and seller populations instead

in Market power and efficiency in a computational electricity market with discriminatory double-auction pricing
by James Nicolaisen, Valentin Petrov, Leigh Tesfatsion 2001
"... In PAGE 16: ... Table VIII corrects a labeling problem in the original Table3 in Nicolaisen et al. [23]: namely, the Table 3 row labeled RCON=1/2 should instead have been labeled RCON=2, and vice versa.... In PAGE 16: ... Table VIII corrects a labeling problem in the original Table 3 in Nicolaisen et al. [23]: namely, the Table3 row labeled RCON=1/2 should instead have been labeled RCON=2, and vice versa. 16 For an example of an oligopoly market in which a switch from individual to social learning results in substantially higher average output, see Vriend [24, Fig.... ..."
Cited by 29

Table 2: Importance factors used for Buyer/Seller, for different levels of preference asymmetry

in Automated Multi-Attribute Negotiation with Efficient Use of Incomplete Preference Information
by Catholijn Jonker, Valentin Robu 2004
"... In PAGE 5: ...presented in Table2 . Note that these are raw importance factors, which are then normalised to add up to 1, using the formula presented in Section 2.... In PAGE 5: ...2 An example negotiation trace In this section, we illustrate the model presented in Section 2 through an example. Here we take the negotiation between a Buyer and Seller with totally asymmetric preferences (see Table2 ), where the only information revealed between parties is the normalised weight of 1 attribute (Tow hedge). For accessories, for both Buyer and Seller, profile 1 is used (see Table 3).... ..."
Cited by 12

Table 2: Importance factors used for Buyer/Seller, for different levels of preference asymmetry

in unknown title
by unknown authors 2004
"... In PAGE 5: ...Table2 . Note that these are raw importance factors, which are then normalised to add up to 1, using the formula presented in Section 2.... In PAGE 5: ...2 An example negotiation trace In this section, we illustrate the model presented in Section 2 through an example. Here we take the negotiation between a Buyer and Seller with totally asymmetric preferences (see Table2 ), where the only information revealed between parties is the normalised weight of 1 attribute (Tow hedge). For accessories, for both Buyer and Seller, profile 1 is used (see Table 3).... ..."
Cited by 12

Table 2: Configurations of importance factors used for Buyer/Seller, for different levels of preference asymmetry

in Automated Multi-Attribute Negotiation with Efficient Use of Incomplete Preference Information
by Catholijn Jonker, Valentin Robu 2004
"... In PAGE 5: ...of asymmetry in preference. The importance factors used are presented in Table2 . Note that these are raw importance factors, which are then normalised to add up to 1, using the formula presented in Section 2.... In PAGE 5: ...2 An example negotiation trace In this section, we illustrate the model presented in Section 2 through an example. Here we take the negotiation between a Buyer and Seller with totally asymmetric preferences (see Table2 ), where the only information revealed between parties is the normalised weight of 1 attribute (Tow hedge). For accessories, for both Buyer and Seller, profile 1 is used (see Table 3).... ..."
Cited by 12

Table 2: Configurations of importance factors used for Buyer/Seller, for different levels of preference asymmetry

in Automated Multi-Attribute Negotiation with Efficient Use of Incomplete Preference Information
by Catholijn Jonker, Valentin Robu
"... In PAGE 5: ...of asymmetry in preference. The importance factors used are presented in Table2 . Note that these are raw importance factors, which are then normalised to add up to 1, using the formula presented in Section 2.... In PAGE 5: ...2 An example negotiation trace In this section, we illustrate the model presented in Section 2 through an example. Here we take the negotiation between a Buyer and Seller with totally asymmetric preferences (see Table2 ), where the only information revealed between parties is the normalised weight of 1 attribute (Tow hedge). For accessories, for both Buyer and Seller, profile 1 is used (see Table 3).... ..."

Table 4: Importance factors used for Buyer/Seller, for different levels of preference asymmetry

in An Agent Architecture for Multi-Attribute Negotiation
by Catholijn M. Jonker, Valentin Robu, Jan Treur 2001
"... In PAGE 20: ... Note that these were also chosen to provide a sufficient cover of the space of possible preferences. The values presented in Table4 are raw importance factors, which are then normalized to add up to 1, using the formula presented in Section 3. Next, we should check that these results hold for different possible value configurations.... In PAGE 21: ...2 An example negotiation trace In this section, we illustrate the model presented in Section 2 through an example. Here we take the negotiation between a Buyer and Seller with totally asymmetric preferences (see Table4 ), where the only information revealed between parties is the normalized weight of 1 attribute (Tow hedge). For accessories, for both Buyer and Seller, profile 1 is used (see Table 5).... In PAGE 25: ... Table 5). Figure 8 plots the outcomes from two test sets: the first one in which the preference weights of both parties are the same across all 4 discrete-valued attributes, the second one in which only two attributes have equal preference weight, the other two having asymmetrical weights (see Table4 for the exact values). Figure 8: (a) Outcomes of the negotiation between a buyer and seller with completely symmetric preferences (i.... In PAGE 25: ...f. Table4 ) From Figure 8, it can be observed that, in fact, for more symmetric preferences revealing more information and/or using guessing does not make too much difference (the tables with the exact outcomes reached are not given here for lack of space, but they point to the same conclusion). In fact, for the case with completely symmetric preferences (Fig.... ..."
Cited by 20

Table 4: Importance factors used for Buyer/Seller, for different levels of preference asymmetry

in An Agent Architecture for Multi-Attribute Negotiation
by Catholijn M. Jonker, Valentin Robu, Jan Treur 2001
"... In PAGE 20: ... Note that these were also chosen to provide a sufficient cover of the space of possible preferences. The values presented in Table4 are raw importance factors, which are ... In PAGE 21: ...2 An example negotiation trace In this section, we illustrate the model presented in Section 2 through an example. Here we take the negotiation between a Buyer and Seller with totally asymmetric preferences (see Table4 ), where the only information revealed between parties is the normalized weight of 1 attribute (Tow hedge). For accessories, for both Buyer and Seller, profile 1 is used (see Table 5).... In PAGE 25: ... Table 5). Figure 8 plots the outcomes from two test sets: the first one in which the preference weights of both parties are the same across all 4 discrete-valued attributes, the second one in which only two attributes have equal preference weight, the other two having asymmetrical weights (see Table4 for the exact values). Figure 8: (a) Outcomes of the negotiation between a buyer and seller with completely symmetric preferences (i.... In PAGE 25: ...f. Table4 ) From Figure 8, it can be observed that, in fact, for more symmetric preferences revealing more information and/or using guessing does not make too much difference (the tables with the exact outcomes reached are not given here for lack of space, but they point to the same conclusion). In fact, for the case with completely symmetric preferences (Fig.... ..."
Cited by 20

Table 3 Within-subjects t tests of time to complete the buyer-seller selection task by display group.

in Motion as an effective flow visualization technique for power systems monitoring and control
by Gavin R. Essenberg, Douglas A. Wiegmann, Thomas J. Overbye, Yan Sun, Contract Pserc, Cornell Wei 2003
Cited by 1
Next 10 →
Results 1 - 10 of 7,702
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University