Reputation’s Agent to ART Testbed Competition Andrew Diniz da Costa firstname.lastname@example.org Roadmap • Competition • Strategy • Important dates • Future works © LES/PUC-Rio 2 Competition • Agent Reputation Trust (ART) Testbed • Competition with agents • AAMAS Conference • Domain: appraisals for paintings • Clients request appraisals for paintings from different eras © LES/PUC-Rio 3 Competition painting * 1 era LES Agent era1 1,0 ... era2 0,1 era9 0,5 Agent 2 Agent 1 era1 era2 ... era10 0,7 era9 era10 era1 © LES/PUC-Rio era2 ... era9 era10 4 Competition • It is necessary to complete the knowledge of each agent • So, transactions with other agents should be executed. • There are two types of transaction: – Opinion – Reputation © LES/PUC-Rio 5 Transactions between agents © LES/PUC-Rio 6 Game • Each game has 20 sessions • When a session finishes: – The true value of the paintings is disclosed. – It is verified what agent got the best appraisals. • In the next session each agent has the following information: – The true value of the paintings – The value of each opinion supplied by other agents – ... • The winner is the agent that has more money in the end of the game © LES/PUC-Rio 7 Important Concepts • Analysis Time – To analyze a painting of a client – Painting of an opinion requested p*=∑i(wi . pi) ∑ i(wi) • Weights – Proper evaluations wi = weight – Opinions of the competitors pi = Evaluation of the opinion • Generation of an opinion requested by another appraiser – Information based in the analysis time – To inform the value © LES/PUC-Rio 8 Strategy • My evaluation has the higher weight (1,0). • To spend a good time to analyze my paintings – Time versus money – How much bigger the time, next 100% of the my knowledge’s grade • It is not enough! © LES/PUC-Rio 9 Strategy ZeCariocaLES Agent era1 Reputations Reputations Agent 1 Agent 2 era2 ... era9 ... Reputations Agent n era10 © LES/PUC-Rio 10 Strategy using opinions • Difference between first and the other sessions • Complement with opinions of other appraisers • I don’t ask if my grade is >= 0,7 • If grade < 0,7 I ask always © LES/PUC-Rio 11 Strategy using opinions • To use opinion like complement • I determine low weights in relation the Zé Carioca agent • Weights to the competitors: 0,1 or 0,3 © LES/PUC-Rio 12 Strategy - weight • If estimates >= 0,5 then weight is 0,3 • If estimates < 0,5 then weight is 0,1 © LES/PUC-Rio 13 Strategy to send opinions • To supply opinion • To spend or not time to supply opinion • To use the Gaussian formula © LES/PUC-Rio 14 Current Agent: First place – Zé Carioca © LES/PUC-Rio 15 Current Agent: Fourth place – Zé Carioca © LES/PUC-Rio 16 LES team • Andrew Diniz, Fábio de Azevedo, Sérgio Ciglione • Improvement of the statisticians – To adjust the weights • Can Reputation transaction help us? © LES/PUC-Rio 17 Important dates • The registration deadline for the 2007 ART Testbed Competition was April 14, 2007 • The agent submission deadline for registered participants is May 9, 2007 • Preliminary Phase - May 10-11, 2007 • Final Round games will be conducted May 16-18, 2007 © LES/PUC-Rio 18 Future works • To compare the ZeCariocaLES agent with the other. • What can we do to improve the agent? • To analyze in which domains the strategy applied can be used. © LES/PUC-Rio 19 References • Agents of the ART-Testbed 2006: – * Iam (University of Nebraska-Lincoln) – Neil (Nanyang Technological University - Singapura) – Frost (Department of Computer Engineering, Bogazici University – Istanbul na Turquia) – Sabatini(GIAA, Universidad Carlos III de Madrid ) – Joey (Computer Science and Engineering, University of Nebraska-Lincoln) – • ... ART Testbed Team. Agent Reputation and Trust Testbed. http://www.lips.utexas.edu/art-testbed/competition_rules.htm http://www.lips.utexas.edu/art-testbed/pdf/SpecSummary.pdf © LES/PUC-Rio 20 References • Fullam, K., T. Klos, G. Muller, J. Sabater, A. Schlosser, Z. Topol, K. S. Barber, J. Rosenschein, L. Vercouter, and M. Voss. (2005) "A Specification of the Agent Reputation and Trust (ART) Testbed: Experimentation and Competition for Trust in Agent Societies," The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS2005), Utrecht, July 25-29, pp. 512-518 • Fullam, K., T. Klos, G. Muller, J. Sabater, Z. Topol, K. S. Barber, J. Rosenschein, and L. Vercouter. (2005) "A Demonstration of The Agent Reputation and Trust (ART) Testbed: Experimentation and Competition for Trust in Agent Societies," The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-2005) Demonstration Track, Utrecht, July 25-29, pp. 151-152. • Sen, S., I. Goswami, and S. Airiau. (2006) "Expertise and Trust-Based Formation of Effective Coalitions: An Evaluation of the ART Testbed," The Workshop on Trust in Agent Societies at The Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS2006), Hakodate, Japan, May 9, pp. 71-78 © LES/PUC-Rio 21 References • Stranders, R. (2006) Argumentation Based Decision Making for Trust in Multi-Agent Systems. Master's Thesis, Delft University of Technology. • Fullam, K. and K.S. Barber. (2006) "Learning Trust Strategies in Reputation Exchange Networks," The Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-2006), Hakodate, Japan, May 8-12, pp. 1241-1248. • Kafali, O. and P. Yolum. (2006) "Trust Strategies for ART Testbed," The Workshop on Trust in Agent Societies at The Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS2006), Hakodate, Japan, May 9, pp. 43-49. • Fernanda Duran, Viviane Torres da Silva, and Carlos J. P. de Lucena (2006) “Using Testimonies to Enforce the Behavior of Agents”. • José de S. P. Guedes Viviane Torres da Silva, and Carlos J. P. de Lucena (2006) “A Reputation Model Based on Testimonies”. © LES/PUC-Rio 22 The End!