Challenges for Trust, Fraud and Deception Research in Multi-agent Systems
Discussions at the 5th Workshop on Deception, Fraud and Trust in Agent Societies held at the 1st International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2002) centered around many important research issues1. This paper attempts to challenge researchers in the community tow...
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| creator | Barber, K. Suzanne Fullam, Karen Kim, Joonoo |
| description | Discussions at the 5th Workshop on Deception, Fraud and Trust in Agent Societies held at the 1st International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2002) centered around many important research issues1. This paper attempts to challenge researchers in the community toward future work concerning three issues inspired by the workshop’s roundtable discussion: (1) distinguishing elements of an agent’s behavior that influence its trustworthiness, (2) building reputation-based trust models without relying on interaction, and (3) benchmarking trust modeling algorithms. Arguments justifying the validity of each problem are presented, and benefits from their solutions are enumerated. |
| doi_str_mv | 10.1007/3-540-36609-1_2 |
| format | Book Chapter |
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Suzanne</creatorcontrib><creatorcontrib>Fullam, Karen</creatorcontrib><creatorcontrib>Kim, Joonoo</creatorcontrib><title>Challenges for Trust, Fraud and Deception Research in Multi-agent Systems</title><title>Lecture notes in computer science</title><description>Discussions at the 5th Workshop on Deception, Fraud and Trust in Agent Societies held at the 1st International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2002) centered around many important research issues1. This paper attempts to challenge researchers in the community toward future work concerning three issues inspired by the workshop’s roundtable discussion: (1) distinguishing elements of an agent’s behavior that influence its trustworthiness, (2) building reputation-based trust models without relying on interaction, and (3) benchmarking trust modeling algorithms. Arguments justifying the validity of each problem are presented, and benefits from their solutions are enumerated.</description><subject>Agent Society</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Autonomous Agent</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Learning and adaptive systems</subject><subject>Reputation Model</subject><subject>Taxi Driver</subject><subject>Trust Model</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540009887</isbn><isbn>3540009884</isbn><isbn>3540366091</isbn><isbn>9783540366096</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2003</creationdate><recordtype>book_chapter</recordtype><recordid>eNotkElv2zAQhdmmLeKkPvfKS29hMlzE5Vi4WQwkCJDlTFDS0FarSCopH_LvS8e-zGDmvRngfYT84HDJAcyVZJUCJrUGx7gXn8iZLIuPmX8mC645Z1Iqd0KWzti9BuCsNV_IAiQI5oyS38jCyUo4MFackmXOf4oJpDBK6AVZr7ah73HYYKZxTPQl7fJ8QW9S2LU0DC39jQ1OczcO9AkzhtRsaTfQh10_dyxscJjp83ue8S1_J19j6DMuj_2cvN5cv6zu2P3j7Xr1655NQsuZWQFYqyCAB9FEF2zUqjaGQ9MKpeuISkTk0RmIMrSlxqrVosZWO20ttvKc_Dz8nUJuQh9TGJou-yl1byG9e15BJbSyxccOvlykki_5ehz_Zs_B79l66Qsu_8HSF7bFz49_0_hvh3n2uD9oSsQU-mYbphlT9hKM4Mp667mR_wHFjnX8</recordid><startdate>20030101</startdate><enddate>20030101</enddate><creator>Barber, K. 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| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2003, Vol.2631, p.8-14 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_15052648 |
| source | Springer Books |
| subjects | Agent Society Applied sciences Artificial intelligence Autonomous Agent Computer science control theory systems Exact sciences and technology Learning and adaptive systems Reputation Model Taxi Driver Trust Model |
| title | Challenges for Trust, Fraud and Deception Research in Multi-agent Systems |
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