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research-article

Choosing a Candidate Using Efficient Allocation of Biased Information

Published: 29 December 2014 Publication History

Abstract

This article deals with a decision-making problem concerning an agent who wants to choose a partner from multiple candidates for long-term collaboration. To choose the best partner, the agent can rely on prior information he knows about the candidates. However, to improve his decision, he can request additional information from information sources. Nonetheless, acquiring information from external information sources about candidates may be biased due to different personalities of the agent searching for a partner and the information source. In addition, information may be costly. Considering the bias and the cost of the information sources, the optimization problem addressed in this article is threefold: (1) determining the necessary amount of additional information, (2) selecting information sources from which to request the information, and (3) choosing the candidates on whom to request the additional information. We propose a heuristic to solve this optimization problem. The results of experiments on simulated and real-world domains demonstrate the efficiency of our algorithm.

References

[1]
M. Abramowitz and I. A. Stegun. 1964. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Dover, New York.
[2]
R. Azoulay-Schwartz and S. Kraus. 2002. Acquiring an optimal amount of information for choosing from alternatives. In Proceedings of the 6th International Workshop on Cooperative Information Agents (CIA’02). Springer-Verlag, 123--137.
[3]
V. A. Cicirello and S. F. Smith. 2005. The max k-armed bandit: A new model of exploration applied to search heuristic selection. In Proceedings of the 20th National Conference on Artificial intelligence (AAAI’05). AAAI Press, 1355--1361.
[4]
V. Conitzer and T. Sandholm. 2003. Definition and complexity of some basic metareasoning problems. In Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI’03). Morgan Kaufmann, 1099--1106.
[5]
R. Dearden, N. Friedman, and S. Russell. 1998. Bayesian q-learning. In Proceedings of the 15th National Conference on Artificial Intelligence (AAAI’98). AAAI Press, 761--768.
[6]
K. K. Fullam and K. S. Barber. 2007. Dynamically learning sources of trust information: Experience vs. reputation. In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’07). ACM, 1641--1648.
[7]
J. Grass and S. Zilberstein. 2000. A value-driven system for autonomous information gathering. Journal of Artificial Intelligence Research (JAIR) 14, 1, 5--27.
[8]
P. Hendrix and B. J. Grosz. 2007. Reputation in the venture games. In Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI’07). AAAI Press, 1866--1867.
[9]
R. Hu and P. Pu. 2010. A study on user perception of personality-based recommender systems. In User Modeling, Adaptation, and Personalization, 18th International Conference (UMAP’10), P. D. Bra, A. Kobsa, and D. N. Chin (Eds.). Lecture Notes in Computer Science Series, vol. 6075. Springer, 291--302.
[10]
T. D. Huynh, N. R. Jennings, and N. R. Shadbolt. 2006. An integrated trust and reputation model for open multi-agent systems. Autonomous Agents and Multi-Agent Systems 13, 2, 119--154.
[11]
P. M. Lee. 1989. Bayesian Statistics: An Introduction. Oxford.
[12]
J. A. Nelder and R. Mead. 1965. A simplex method for function minimization. Computer Journal 7, 308--313.
[13]
J. M. Pujol, R. Sangüesa, and J. Delgado. 2002. Extracting reputation in multi agent systems by means of social network topology. In Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’02). ACM Press, 467--474.
[14]
S. D. Ramchurn, D. Huynh, and N. R. Jennings. 2004. Trust in multi-agent systems. The Knowledge Engineering Review 19, 1, 1--25.
[15]
S. D. Ramchurn, C. Sierra, L. Godo, and N. Jennings. 2003. A computational trust model for multi-agent interactions based on confidence and reputation. In Proceedings of the 6th International Workshop of Deception, Fraud and Trust in Agent Societies. 69--75.
[16]
S. Reches, P. Hendrix, S. Kraus, and B. J. Grosz. 2008. Efficiently determining the appropriate mix of personal interaction and reputation information in partner choice. In Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’08). IFAAMAS Press, 583--590.
[17]
S. Reches, M. Kalech, and P. Hendrix. 2013. A framework for effectively choosing between alternative candidate partners. ACM Transactions on Intelligent Systems and Technology 5, 2, Article 30.
[18]
S. Reches, S. Talman, and S. Kraus. 2007. A statistical decision-making model for choosing among multiple alternatives. In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’07). ACM Press, 2051--2053.
[19]
S. Reece, S. Roberts, A. Rogers, and N. R. Jennings. 2007a. A multi-dimensional trust model for heterogeneous contract observations. In Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI’07). AAAI Press, 128--135.
[20]
S. Reece, A. Rogers, S. Roberts, and N. R. Jennings. 2007b. Rumours and reputation: evaluating multi-dimensional trust within a decentralised reputation system. In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’07). ACM Press, 1--8.
[21]
K. Regan, R. Cohen, and P. Poupart. 2005. The advisor-pomdp: A principled approach to trust through reputation in electronic markets. In Proceedings of the 3rd Annual Conference on Privacy, Security and Trust (PST’05).
[22]
M. Rehak, E. Staab, M. Pechoucek, J. Stiborek, M. Grill, and K. Bartos. 2009. Dynamic information source selection for intrusion detection systems. In Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’09). IFAAMAS Press, 1009--1016.
[23]
F. Scheid. 1989. Schaum’s Outline of Numerical Analysis. Schaum’s Outline Series. McGraw-Hill Education.
[24]
B. Selman and H. A. Kautz. 1993. An empirical study of greedy local search for satisfiability testing. In Proceedings of the 11th National Conference on Artificial Intelligence (AAAI’93). AAAI Press, 46--51.
[25]
S. Singer and J. Nelder. 2009. Nelder-mead algorithm. Scholarpedia 4, 7, 2928.
[26]
B. Smyth, M. Coyle, and P. Briggs. 2011. Communities, collaboration, and recommender systems in personalized web search. In Recommender Systems Handbook, F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor (Eds.). Springer, 579--614.
[27]
M. J. Streeter and S. F. Smith. 2006. An asymptotically optimal algorithm for the max k-armed bandit problem. In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI’06). AAAI Press, 135--142.
[28]
S. Talman, R. Toester, and S. Kraus. 2005. Choosing between heuristics and strategies: an enhanced model for decision-making. In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI’05). Professional Book Center, 324--330.
[29]
W. T. Teacy, J. Patel, N. R. Jennings, and M. Luck. 2006. Travos: Trust and reputation in the context of inaccurate information sources. Autonomous Agents and Multi-Agent Systems 12, 2, 183--198.
[30]
W. T. L. Teacy, G. Chalkiadakis, A. Rogers, and N. R. Jennings. 2008. Sequential decision making with untrustworthy service providers. In Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’08). IFAAMAS Press, 755--762.
[31]
W. T. L. Teacy, J. Patel, N. R. Jennings, and M. Luck. 2005. Coping with inaccurate reputation sources: experimental analysis of a probabilistic trust model. In Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’05). ACM, 997--1004.
[32]
M. Vanzin and K. Barber. 2006. Decentralized partner finding in multi-agent systems. In Coordination of Large-Scale Multiagent Systems, P. Scerri, R. Vincent, and R. Mailler (Eds.). Springer, 75--98.
[33]
Y. Wang, C.-W. Hang, and M. P. Singh. 2011. A probabilistic approach for maintaining trust based on evidence. Journal of Artificial Intelligence Research (JAIR) 40, 1, 221--267.
[34]
G. Zacharia and P. Maes. 2000. Trust management through reputation mechanisms. Applied Artificial Intelligence 14, 9, 881--907.

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Published In

cover image ACM Transactions on Intelligent Systems and Technology
ACM Transactions on Intelligent Systems and Technology  Volume 5, Issue 4
Special Sections on Diversity and Discovery in Recommender Systems, Online Advertising and Regular Papers
January 2015
390 pages
ISSN:2157-6904
EISSN:2157-6912
DOI:10.1145/2699158
  • Editor:
  • Huan Liu
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 December 2014
Accepted: 01 November 2013
Revised: 01 November 2013
Received: 01 February 2013
Published in TIST Volume 5, Issue 4

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  1. Decision theory
  2. multiagent systems

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