Kun Chang Lee and Namho Lee (2007)
CARDS: Case-Based Reasoning Decision Support Mechanism for Multi-Agent Negotiation in Mobile Commerce
Journal of Artificial Societies and Social Simulation
vol. 10, no. 2, 4
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Received: 01-Nov-2004 Accepted: 01-Jan-2007 Published: 31-Mar-2007
|Figure 1. Schematic diagram of CARDS architecture|
where Nj indicates jth attribute value of a new case ( j =1,2,…,n), and Sijdenotes jth attribute value of ith case in the case base of CBR ( i =1,2,…, m). Netlogo source code for implementing the CBR function of CARDS using SI is listed in Table 1. N1,…, N4 are attributes of cases (N1 : Current inventory level, N2 : remaining period of validity, N3 : freshness level, N4 : number of potential buyers within reasonable range of distance from store). Table 1 describes how the case based reasoning performs.
to change-CBR-price locals [temp_t temp_i temp_si temp_optimal_si temp_item] set temp_t(1) repeat seller_number [ ask seller with [reg_number = temp_t and mobile_service = 1 and CARDS_service = 1 ] set temp_i (0) repeat length CBR_price [ set temp_si sqrt((N1_Current_Value - item (temp_i) CBR_N1_List) ^ 2 + ((N2_Current_Value - item (temp_i) CBR_N2_List) ^ 2 + (N3_Current_Value - item (temp_i) CBR_N3_List) ^ 2 + (N4_Current_Value - item (temp_i) CBR_N4_List) ^ 2) if (temp_i = 0)[set temp_optimal_si (temp_si) set temp_item (temp_i)] if (temp_i >= 1) [ if(temp_si < temp_optimal_si) [set temp_optimal_si (temp_si) set temp_item (temp_i )] ] set temp_i (temp_i + 1) ] set offer_product_price (item temp_item CBR_price) ] set temp_t(temp_t + 1) ] end
|Table 1. CBR function of CARDS|
Ui denotes ith buyer's utility, Wij buyer's preference for jth utility factor, and Fij ith buyer's jth utility factor. It is certain that . Examples of utility factors include not only price, product, and quality, but also contextual information such as the buyer's current location and environmental constraints. As shown in Table 5, we consider five factors such as F1:Distance, F2:Freshness, F3:Category, F4:Price, F5:Timeliness. Therefore, five weights W1 ∼ W5 are assigned to each factor. Table 2 shows Netlogo source code for calculating the B-agent's utility function.
;; to Calculate-Util set temp (1) set temp_id (1) repeat customer_number [ ask customer with [reserve != 1 and id_number = temp_id] [ set temp_distance (p_distance ) set temp_price (p_price ) set temp_time (p_time ) set temp_customer_x (current_x) set temp_customer_y (current_y) set utility (0) set temp_selected_seller (0) repeat seller_number [ ask seller in-radius-nowrap (remaining_time / time_per_patch) with [available_product_number > 0 and reg_number = temp1][ set actual_distance (abs (sqrt((temp_customer_x - location_x) ^ 2 + (temp_customer_y - location_y) ^ 2 ) )) ;; Convert_factor_point set temp_util ( temp_W1 * temp_point_F1 + temp_W2 * temp_point_F2 + temp_W3 * temp_point_F3 + temp_W4 * temp_point_F4 + temp_W5 * temp_point_F5) if (temp_util > utility) [ set utility (temp_util) set temp_selected_seller (reg_number) ] ] set temp1 (temp1 + 1)] set temp1 (1) set utility_without_mobile (utility) set normal_selected_seller (temp_selected_seller) ] set temp_id (temp_id + 1) ] end
|Table 2. B-agent's utility calculation|
ask buyer with [deal !=1 ] [ set goal_utility (Current_utility + (utility_adjustment / 100) * Current_utility ) set temp (selected_buyer) ask seller with [reg_number = temp ][ if (available_product_number > 0) [ if (p_temp > 0 ) [ set temp_price_down_request int((goal_utility - Current_utility) / p_temp) ]]]
|Table 3. B-agent's price update process|
|Figure 2. Logical diagram showing how CARDS works to coordinate between sellers and buyers|
to give-offer-to-CARDS-buyer locals [temp] ask customer [set negotiating_shop_list ] ask shop with [unsold_product_number > 0 and mobile_service = 1 ] [ set temp (reg_number) without-interruption [ foreach negotiating_customer_list [ ask customer with [id_number = ? and reserve != 1 and mobile_service = 1] [set negotiating_shop_list lput temp negotiating_shop_list ] ] ] ] end to nego-offer-to-shop [remaining_time] locals [temp temp_id temp_seller_no temp_no actual_distance ] set temp_no (1) ask shop [set mss_nego_custom_list ] repeat customer_number [ ask customer with [id_number = temp_no][ if ( reserve != 1 and CARDS_service = 1) [ set temp_id (id_number) ask shop in-radius-nowrap (remaining_time / time_per_patch) with [unsold_product_number > 0 and CARDS_service = 1] [set CARDS_nego_custom_list lput temp_id CARDS_nego_custom_list ] ] ] set temp_no (temp_no + 1) ] end
|Table 4. CARDS negotiation processing process|
Depending on the situation that the potential buyer is facing at the time, the utility is determined as follows (Table 5).
|Table 5: Buyer's utility|
|Utility factor||Condition||Converted utility|
|Distance (D)||Within 20 minutes |
Within 30 minutes
Within 40 minutes
Within 50 minutes
More than 60 minutes
|Category (C)||Preferred category |
|Price (P)||Price negotiation||50 - (new price/list price) * 50|
|Timeliness (T)||If the buyer wants the product on offer |
|Figure 3. CARDS prototype implemented on Netlogo|
which is derived from the utility function
and send the adjusted price to the S-agents as a counter-offer. By consulting with CBR, S-agents determine whether to accept the counter-offer or not. If output attribute is 1, then the S-agents accept the counter-offer. Otherwise, the counter-offer is rejected.
|(a) Buyer's average utility curve|
|(b) Seller's average profit|
|Figure 4. Average utility and profit curves|
|Table 6: Simulation results for three mobile groups|
|Simulation Round||Buyer's Average Utility||Seller's Average Profit|
|Non-Mobile Group||Passive-Mobile Group||Active-Mobile Group||Non-Mobile Group||Passive-Mobile Group||Active-Mobile Group|
|Table 7a: F-test for buyer's utility|
|Sum of Squares||df||Mean Square||F||Sig.|
|Table 7b: F-test for seller's profit|
|Sum of Squares||df||Mean Square||F||Sig.|
ANDERSEN K V, Forgegren-pedersen A, Varshney U (2003), Mobile organizing using information technology (MOBIT). Information Communication and Society, 6 (2), pp.211-228.
APPLEGATE L M, Holsapple C W, Kalakota R, Radermacher F J and Whinston A B (1996). Electronic commerce: Building blocks of new business opportunity, Journal of Organizational Computing & Electronic Commerce, 6(1), pp.1-10.
BAILEY M N and Lawrence R L (2001). Do we have a new economy? American Economic Review, 91(2), pp. 308-312.
CABRI G, Leonardi L, Mamei M, and Zambonelli F (2003). Location-dependent services for mobile users, IEEE Transactions on Systems, 33(6), pp. 667-681.
CHANG H C, Dong L, Liu F X and Lu W F (2000). Indexing and retrieval in machining process planning using case-based reasoning. Artificial Intelligence in Engineering, 14(1), pp.1-13.
CHIU C (2002). A case-based customer classification approach for direct marketing. Expert Systems with Applications, 22(2), pp. 163-168.
CHUA D K H, Li D Z (2001). Case-Based Reasoning Approach in Bid Decision Making. Journal of Construction Engineering & Management, 127(1), pp.35-44
CLARKE I (2001). Emerging value propositions for m-commerce. Journal of Business Strategies, 18(2), pp.133-148.
COOPER S and Taleb-Bendiab A (1998). CONCENSUS: Multi-party negotiation support for conflict resolution in concurrent engineering design. Journal of Intelligent Manufacturing, 9(2), pp. 155-159.
COURSARIS C and Hassanein K (2002) Understanding m-commerce. Quarterly Journal of Electronic Commerce, 3(3), pp. 247-271.
EDWARDS W K, Newman M W, Sedivy J Z and Smith T F (2004). Supporting serendipitous integration in mobile computing environments. International Journal of Human-Computer Studies, 60, pp. 666-700.
ESYIN C and Mustapha S M F D S (2004). Negotiation in a multi-dimensional CBR system, Cybernetics and Intelligent Systems, 2004 IEEE Conference, 2, pp.1192 - 1195
GAYESKI D M (2002), Learning Unplugged. American Management Association, New York, New York.
GEBAUER J and Shaw M J (2004). Success factors and impacts of mobile business applications: results from a mobile e-procurement study. International Journal of Electronic Commerce. 8 (3), pp.19-41.
GUAN S, Ngoo C S, Zhu F (2002). Handy broker: an intelligent product-brokering agent for m-commerce applications with user preference tracking, Electronic Commerce Research and Applications, 1(3), pp. 314-330.
HARGREAVES D, Knight T, Brownsword P and Macdonald D (2003), real-time emergency management via satellite: Status update and future directions. ISPRS Journal of Photogrammetry and Remote Sensing, 57(4), pp. 273-280.
HAQUE B U, Elecheanu R A, Barson R J and Pawar K S (2000). Toward the application of case based reasoning to decision-making in concurrent product development (concurrent engineering), Knowledge-Based Systems, 13(2-3),pp. pp.101-112.
HERZBERG A, (2003). Payments and banking with mobile personal devices. Communications of the ACM, 46 (5), pp.53-58.
HOGG L M I and Jennings N R (2001). Socially intelligent reasoning for autonomous agents. IEEE Transactions on Systems, Man, & Cybernetics Part A: Systems & Humans, 31(5), pp. 381-393.
HSU C I, Chiu C and Hsu P L (2004). Predicting information systems outsourcing success using a hierarchical design of case-based reasoning, Expert Systems with Applications, 26(3),pp. 435-441.
JUNG C, Han I and Suh, B (1999). Risk analysis for electronic commerce using case-based reasoning. International Journal of Intelligent Systems in Accounting, Finance and Management, 8(1), pp. 61-73.
KAVASSALIS P, Spyropoulou N, Drossos D., Mitrokostas E, Gikas G and Hatzistamatiou A (2003). Mobile permission marketing: Faming the market inquiry. International Journal of Electronic Commerce, 8(1) pp. 55-79.
KOLODNER J (1993). Case-Based Reasoning. San Ma-teo, CA: Morgan Kaufmann
LIANG T P and Wei C P (2004), Introduction to the Special Issue: Mobile Commerce Applications, International Journal of Electronic Commerce, 8(3), pp.7-17
LIAO S H (2000). Case-Based decision support system: architecture for simulating military command and control, European Journal of Operational Research, 123(3), pp. 558-567.
LIAO T W, Zhang Z M and Mount C R (2000). A case-based reasoning system for identifying failure mechanisms, Engineering Applications of Artificial Intelligence, 13(2), pp.199-213.
LOONEY C A, Jessup L M , Valacich J S (2004). Emerging business models for mobile brokerage services. Communications of the ACM, 47 (6), pp.71-77.
LOTTAZ C, Smith I F C, Robert-Nicoud Y, and Faltings B V (2000) Constraint-based support for negotiation in collaborative design, Artificial Intelligence in Engineering, 14(3), pp. 261-280.
LUO X, Zhang C, and Leung H F (2001) Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment: A case study. International Journal of Approximate Reasoning, 27(1), pp. 27-59.
MALLAT N, Rossi M, Tuunainen V K (2004). Mobile banking services. Communicates of the ACM 47, (5), pp.42-46.
MANDRY T, Pernul G, and Rohm A W (2001) Mobile agents in electronic markets: opportunities, risks, agent protection, International Journal of Electronic Commerce, 5(2), pp. 47-60.
MCMULLEN P R (2001) An ant colony optimization approach to addressing a JIT sequencing problem with multiple objectives, Artificial Intelligence in Engineering, 15(3), pp. 309-317.
MIAH T and Bashir O (1997) Mobile workers: Access to information on the move. Computing and Control Engineering, 8, pp.215-223.
NAH F, Siau K, Sheng H (2005). The value of mobile applications: a study on a public utility company. Communications of the ACM, 48 (2), 85-90.
NGAI E W T and Gunasekaran A (2005). A review for mobile commerce research and applications, Decision Support Systems, available online at www.sciencedirect.com.
NOH J B, Lee K C, Kim J K, Lee J K and Kim S H (2000). A case based reasoning approach to cognitive map-driven tacit knowledge management. Expert Systems with Applications, 19(4), pp. 249-259.
OMICINI A and Zambonelli F (1988) Co-ordination of mobile information agents in Tucson, Internet Research: Electronic Networking Applications and Policy, 8(5), pp. 400-413.
PARK C S, Han I (2002). A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction, Expert Systems with Applications, 23(3), pp.255-264.
PAUROBALLY S, Turner P J, Jennings N R (2003), Automating negotiation for m-services, IEEE Transactions on Systems, Man and Cybernetics, Part A 33 (6), pp.709-724.
PERSSON P, Laaksolahti J, and Lonngvist P (2001). Understanding Socially intelligent Agents - A Multilayered Phenomenon. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 31(5), pp. 349-360.
PORN L M and Patrick K (2002). Mobile computing acceptance grows as applications evolve. Healthcare Financial Management, 56(1), pp.66-70.
PRUTHIKRAI M H, Wen J and Lim B (2005), Consumer-based m-commerce: exploring consumer perception of mobile applications, Computer Standards & Interfaces, 27(4), pp.347-357
RODGERA J A and Pendharkarp P C (2004). A field study of the impact of gender and user's technical experience on the performance of voice-activated medical tracking application. International Journal of Human-Computer Studies, 60, pp.529-544.
SADEH N (2002). M-Commerce: Technologies, Services, and Business Models. Wiley, USA .
SADEK A W, Smith B L and Demetsky M J (2001). A prototype case-based reasoning system for real-time freeway traffic routing, Transportation Research Part C: Emerging Technologies, 9(5), pp. 353-380.
SCHMIDT G (1998). Case-based reasoning for production scheduling, International Journal of Production Economics, 56-57, pp.537-546.
SEAGER A (2003). M-commerce: An integrated approach. Telecommunications International, 37(2), pp.36.
STENDER M and Ritz T (2006). Modeling of B2B mobile commerce processes. International Journal of Production Economics, 101(1), pp.128-139
SENN J A (2000). The emergence of M-Commerce. Computer, 33(12), pp. 148-150.
SIAU K, Sheng H, Nah F (2003). Developing a Framework for Trust in Mobile Commerce Proceedings of the Second Annual Workshop on HCI Research in MIS, Seattle, WA 2003, pp.85-89.
SIAU K, Sheng H, Nah F (2004a). The Value of Mobile Commerce to Customers Proceedings of the Third Annual Workshop on HCI Research in MIS, Washington, DC
SIAU K, Sheng H, Nah F, Davis S (2004b). A qualitative investigation on consumer trust in mobile commerce. International Journal of Electronic Business, 2 (3), pp.283-300.
SILLINCE J A A and Saeedi M H (1999). Computer-mediated communication: Problems and potentials of argumentation support systems. Decision Support Systems, 26(4), pp. 287-306.
SOUMITRA D, Berend W, and Arco D (1997), Case-Based Reasoning Systems: From Automation to Decision-Aiding and Stimulation, IEEE Transactions On Knowledge And Data Engineering, 9(6) pp.911-922
TSANG, M M., Ho S C and Liang T P (2004). Consumer attitudes toward mobile advertising: An empirical study. International Journal of Electronic Commerce, 8(3), pp.65-78
TUNG B and Lee J (1999). An agent-based framework for building decision support systems, Decision Support Systems, 25(3), pp.225-237.
TURISCO F (2000). Mobile computing is next technology frontier for healthcare providers. Healthcare Financial Management, 54(11), pp.78-80.
YUAN Y and Zhang J J (2003). Towards an appropriate business model for m-commerce. International Journal of Mobile Communications, 1(2) , pp.35-56.
ULIERU M, Norrie D, Kremer R, and Shen W (2000). A multi-resolution collaborative architecture for web-centric global manufacturing. Information Sciences, 127(1-2), pp. 3-21.
VARMA A, Roddy N (1999). ICARUS: Design and deployment of a case-based reasoning system for locomotive diagnostics. Engineering Applications of Artificial Intelligence, 12(6), pp. 681-690.
VARSHNEY U (1999). Networking support for mobile computing, Communications of AIS, 1(1), pp.1-30.
VARSHNEY U (2001). Location management support for mobile commerce applications. In Proceedings of the 1st International Workshop on Mobile Commerce. New York: ACM Press, 2001, pp.1-6.
VARSHNEY U and Vetter R (2001). A framework for the emerging mobile commerce applications, In Proceedings of the 34th Annual Hawaii International Conference on System Sciences.
VARSHNEY U and Vetter R (2002). Mobile commerce: Framework, applications and net-working support. Mobile Networks and Applications, 7. pp.185-198.
WANG Y, Tan K L, and Ren J (2002). A study of building Internet marketplaces on the basis of mobile agents for parallel processing. World Wide Web, 5(1), pp. 41-66.
WILKE W, Bergman R and Wess S (1998). Negotiation During Intelligent Sales Support with CBR, Proceedings of the 6th German workshop on Case Based Reasoning, GWCBR'98
WOOLDRIDGE M (1997). Agent based software engineering, IEEE Proceedings of Software Engineering, 144(1), pp. 26-37.
WOOLDRIDGE M and Jennings N (1995). Intelligent agents: Theory and practice. The Knowledge Engineering Review, 10(2), pp. 115-152.
WU D J (2001). Software agents for knowledge management: Coordination in multi-agent supply chains and auctions. Expert Systems with Applications, 20(1), pp. 51-64.
YANG, B S, Han T H and Kim Y S (2004). Integration of art-Kohonen neural network and case-based reasoning for intelligent fault diagnosis, Expert Systems with Applications, 26(3), pp. 387-395.
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