Multi-Agent Systems Research PhD Workshop 2008 -- Reading List

Useful article in preparation for your workshop presentation: How to present a research paper? by Matthew O. Jackson.

Day 1: Mon Jan 21 Morning	Introduction to Multi-Agent Systems Research: Intelligent Agents, Agent architectures, and Agent Modeling Required readings:
9:00-10:30	Lecture: Wolf Ketter, Introduction to Intelligent Agents and Multi-Agent Systems
10:30-12:00	Lecture: Wolf Ketter, Multiagent Interactions: Utilities and Preferences, Multiagent Encounters, Strategies and Equilibria
Speakers
9:00-10:30	Wolf Ketter - Lecture notes on Introduction to Intelligent Agents
10:30-12:00	Wolf Ketter - Lecture notes Multiagent Interactions Additional material: Chapter 2 of Russell and Norvig, "Artificial Intelligence. A modern approach" is devoted to agent architectures. for more definitions of what an agent is, read: Stan Franklin and Art Graesser "Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agent," Proc. of the Third International Workshop on Agent Theories, Architectures, and Languages, published as Intelligent Agents III, Springer-Verlag, 1997, pp 21-35. For a cognitive perspective on agents, read: Ronald J. Brachman, "Systems That Know What They're Doing," IEEE Intelligent Systems, vol 17, n 6, Nov-Dec 2002. For a basic and short introduction to game theory read David K. Levine, What is Game Theory? Department of Economics, UCLA or the short but more detailed paper David K. Levine Game Theory or the longer but easy to read class notes Roger McCain, " Strategy and Conflict: An Introductory Sketch of Game Theory" For a long paper on adjustable autonomy, read: Scerri, P., Pynadath, D.V., Tambe, M. (2002) " Towards Adjustable Autonomy for the Real World", JAIR, Volume 17, pages 171-228.
Day 1: Mon Jan 21 Afternoon	Reaching Agreements: Mechanism Design and Online Auctions Required readings:
13:00-15:40	Lecture: Eric van Heck
15:40-16:20	T. Sandholm, Algorithm for Optimal Winner Determination in Combinatorial Auctions. Artificial Intelligence, Vol 135, pp 1-54, 2002.
16:20-17:00	Bapna, R. and Goes, P. and Gupta, A. and Jin, Y. User heterogeneity and its impact on electronic auction market design: An empirical exploration, MIS Quarterly, 28(1): 2004, 21--43.
Speakers
13:00-15:40	Eric van Heck - Lecture notes on Online Auctions
15:40-16:20	Milan Lovric - Lecture notes on Paper 1
16:20-17:00	Annie Yang - Lecture notes on Paper 2 Additional material on Mechanism Design and Auctions: The classical survey on combinatorial auctions Sven de Vries and Rakesh Vohra, Combinatorial auctions: a survey, 2000. A description of bidding languages and how they affect the complexity of combinatorial auctions is in Noam Nisan, " Bidding and Allocation in Combinatorial Auctions," Tech Report, Institute of Computer Science, Hebrew University, 2000. for a detailed description of the FCC spectrum auctions, read Robert Weber, Making More from Less: Strategic Demand Reduction in the FCC Spectrum Auctions, The Journal of Economics and Management Strategy 6(3), 1997. Martin Pesendorfer, A Study of Collusion in First-Price Auctions, Review of Economic Studies, Volume 67, Number 3, pp 381-411, July 2000. For a description of an extensive test suite for combinatorial auctions, read: Leyton-Brown, Shoham. " Test Suite for Combinatorial Auctions" Chapter 18 in Combinatorial Auctions, P. Cramton, Y. Shoham, R. Steinberg (eds.), MIT Press, 2006. For a description of real applications of combinatorial auctions, read Tuomas Sandholm, Expressive Commerce and Its Application to Sourcing: How We Conducted $35 Billion of Generalized Combinatorial Auctions. AI Magazine, 28(3), 45-58, Fall 2007. The patent for the ZIP algorithms. Luke Hunsberger and Barbara J. Grosz, 2000. A Combinatorial Auction for Collaborative Planning, (ps) Proc 4th Int'l Conf. on Multi-Agent Systems, Boston, MA pp. 151-158.
18:30-20:30	Workshop dinner at Oliva.
Day 2: Tue Jan 22 Morning	Multi-agent learning Required reading:
9:00-10:30	Lecture: Wolf Ketter
10:40-11:20	Sandholm, T. 2007. Perspectives on Multiagent Learning. Artificial Intelligence, 171 (7), 382-391.
11:20-12:00	Y. Shoham, R. Powers and T. Grenager. If Multi-Agent Learning is the Answer, What is the Question? Artificial Intelligence 171(7), pages 365-377,
Speakers
9:00-10:30	Wolf Ketter - Lecture notes on Multi-Agent Learning
10:40-11:20	Rui de Almeida - Lecture notes on Paper 1
11:20-12:00	Jordan Srour - Lecture notes on Paper 2 Additional material: Peter Stone's rebuttal to Shoham paper. Peter Stone, Multiagent learning is not the answer. It is the question. Artificial Intelligence, Volume 171, Issue 7, May 2007, Pages 402-405. Another algorithm for multi-agent learning: Jelle R. Kok and Nikos Vlassis, Sparse cooperative Q-learning. Proc. of the 21st Int. Conf. on Machine Learning, pp. 481-488, ACM, Banff, Canada, July 2004. Learning in games: R. Powers and Y. Shoham. Learning Against Opponents with Bounded Memory. Proc of IJCAI 2005. R. Powers and Y. Shoham. New Criteria and a New Algorithm for Learning in Multi-Agent Systems. Proceedings of NIPS-2004/5. Michael L. Littman, Markov games as a framework for multi-agent reinforcement learning, 1994. Proc. 11th Int'l Conference on Machine Learning, pages 157--163. Michael L. Littman, Friend-or-Foe Q-learning in General-Sum Games, 2001. Proc. 18th Int'l Conference on Machine Learning, pages 322--328.
Day 2: Tue Jan 22 Afternoon	Part 1: Working together: Task allocation, scheduling, and distributed problem solving Part 2: Application: Agents in Supply-Chain Management Simulation Required reading:
13:00-15:00	Lecture: Wolf Ketter
15:00-15:40	Davis, R. and Smith, R. Negotiation as a Metaphor for Distributed Problem Solving, Artificial Intelligence 20, pp. 63-109.
15:40-16:20	Wolfgang Ketter, John Collins, Maria Gini, Alok Gupta, and Paul Schrater. Detecting and Forecasting Economic Regimes in Multi-Agent Automated Exchanges Decision Support Systems, -(-):Conditionally accepted. Second round of reviewing, 2008.
16:20-17:20	Swaminathan J., Smith S., Sadeh N. Modeling supply chain dynamics: A multiagent approach. Decision Sciences. Vol. 29 (3), pp. 607-632.
Speakers
13:00-15:00	Wolf Ketter Lecture slides
15:00-15:40	Lars Nielsen - Lecture notes on Paper 1
15:40-16:20	Carsten Block - Lecture notes on Paper 2
16:20-17:00	Mi Zhang - Lecture notes on Paper 3 Additional material: Paul Scerri, A Farinelli, Steven Okamoto, Milind Tambe, Allocating tasks in extreme teams, 4th Int'l Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2005 Milind Tambe, E. Bowring, E. Pearce, P. Varakantham, P. Scerri, and D. V. Pynadath, Electric Elves: What went wrong and why, AI Magazine (to appear) P. Berry, M. Gervasio, T. Uribe, M. Pollack, M. Moffitt. A Personalized Time Management Assistant, AAAI 2005 Spring Symposium Series, Stanford, CA, Mar 2005. for more details on the provacy loss describes in the Electric Elves paper read R. T. Maheswaran, J. P. Pearce, P. Varakantham, E. Bowring and M. Tambe, Valuation of Possible States (vps): A Unifying Quantitative Framework for Analysis of Privacy Loss in Collaboration," Proc. 4th Int'l Conference on Autonomous Agents and Multi-Agent Systems", Utrecht, The Netherlands, 2005. Another approach to resource allocation: Aram Galstyan, Shashikiran Kolar, and Kristina Lerman, Resource allocation games with changing resource capacities, 2nd Int'l Conf. on Autonomous Agents and Multiagent Systems, pp 145-152, 2003. Coalition formation for allocation of tasks O. Shehory and S. Kraus. Feasible Formation of Stable Coalitions among Autonomous Agents in Non-super-additive Environments, Computational Intelligence, 15(3):218--251, 1999.
Day 3: Wed Jan 23 Morning	Applications: Agents for Information Retrieval and Management and Agents for Electronic Commerce Required reading:
9:00-9:20	Lecture Wolf
9:20-10:00	Jung S.Y., Hong J., and Kim T. A Statistical Model for User Preference. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, Vol. 17, No. 6, June 2005.
10:00-10:40	Rhodes B.J & Maes P. Just-in-time information retrieval agents. IBM Systems Journal. Volume 39, Numbers 3 & 4, pp. 685-704.
10:40-11:20	Xiao B. & Benbasat E-COMMERCE PRODUCT RECOMMENDATION AGENTS: USE, CHARACTERISTICS, AND IMPACT. MIS Quarterly. Vol. 31, No. 1, pp. 137-209.
11:20-12:00	Montgomery A.L., Hosanagar K., Krishnan R. & Clay K.B. Designing a Better Shopbot MANAGEMENT SCIENCE. Vol. 50, No. 2, February 2004, pp. 189-206.
Speakers
9:00-9:20	Lecture Wolf
9:20-10:00	Carsten Block - Lecture notes on A Statistical Model for User Preference.
10:00-10:40	Timothy Broesamle - Lecture notes on Just-in-time information retrieval agents.
10:40-11:20	Annie Yang - Lecture notes on E-COMMERCE PRODUCT RECOMMENDATION AGENTS: USE, CHARACTERISTICS, AND IMPACT.
11:20-12:00	Milan Lovic - Lecture notes on Designing a Better Shopbot Additional material: Wan Y., Menon S. & Ramaprasad A. A classification of product comparison agents. Communications of the ACM, Volume 50 , Issue 8, Pages: 65 - 71, August 2007. Ravi Arona, Arun Sundararajan, Siva Viswanathan Intelligent agents in electronic markets for information goods: customization, preference revelation and pricing Decision Support Systems, Volume 41, Issue 4, Pages: 764--786, 2006. Hendler J. Agents and the Semantic Web.IEEE INTELLIGENT SYSTEMS. Vol. 16, No. 2, pp. 30-37. Schiaffino S. & Amandi A. Polite Personal Agents.IEEE INTELLIGENT SYSTEMS. Vol. 21, No. 1, pp. 12-19.
Day 3: Wed Jan 23 Afternoon	Financial Markets and Logistics/Transportation Agents Required reading:
13:00-15:00	Guest lecture by Uzay Kaymak on Agent-based simulation of financial markets
	Katalin Boer, Uzay Kaymak, and Jaap Spiering. FROM DISCRETE-TIME MODELS TO CONTINUOUS-TIME, ASYNCHRONOUS MODELING OF FINANCIAL MARKETS Computational Intelligence 2007.
15:00-17:00	Guest lecture by Rob Zuidwijk on Agents in logistics and supply chain management
	V. Marik and D. McFarlane Industrial Adoption of Agent-Based Technologies IEEE Intelligent Systems 20 (2005) (1), pp. 27 - 35.
Speakers
13:00-15:00	Uzay Kaymak: Lecture notes
15:00-17:00	Rob Zuidwijk: Lecture notes Additional material: Davidsson P, Henesey L, Ramstedt L, Tornquist J, Wernstedt F, An analysis of agent-based approaches to transport logistics. Transportation Research Part C: Emerging Technologies, Vol. 13 (4), pp. 255-271.
Day 4: Mon Mar 10 Morning	Emergent Behaviors Required reading:
9:00-9:20	Opening of Part 2: Wolf Ketter .
9:20-10:00	Joshua Epstein, Agent-Based Computational Models And Generative Social Science , Complexity 4/5, John Wiley, 1999.
10:00-10:40	Justin Werfel and Radhika Nagpal, Extended Stigmergy in Collective Construction, IEEE Intelligent Systems 21(2): 20-28 (2006).
10:40-11:20	Guest lecture by Ludo Waltman
11:20-12:00	Alexander Babanov, Wolfgang Ketter, and Maria Gini. An Evolutionary Framework for Determining Heterogeneous Strategies in Multi-Agent Marketplaces, ERIM Research Report Series, 2008
Speakers
9:00-9:20	Wolf Ketter
9:20-10:00	Timothy Broesamle - Lecture slides
10:00-10:40	Jordan Srour - Lecture slides
10:40-11:20	Ludo Waltman - Lecture slides
11:20-12:00	Rui de Almeida - Lecture slides Additional material: Here are some of the many papers on robot swarms by the same authors: Justin Werfel, Yaneer Bar-Yam, Radhika Nagpal, Building Patterned Structures with Robot Swarms, Int'l. Joint Conference on Artificial Intelligence (IJCAI '05), August 2005. Jimming Cheng, Winston Cheng, Radhika Nagpal, Robust and Self-repairing formation control for swarms of mobile agents National Conference on Artificial Intelligence (AAAI '05), July 2005. Jonathan Bachrach, Radhika Nagpal, Micheal Salib, Howard Shrobe, Experimental Results and Theoretical Analysis of a Self-Organizing Global Coordinate System for Ad Hoc Sensor Networks, Telecommunications Systems Journal, Special Issue on Wireless System Networks, Kluwer Academic Publishing, 2003. a paper on a physics-oriented model for achieving cooperation in large-scale systems: O. Shehory, S. Kraus and O. Yadgar. Emergent cooperative goal-satisfaction in large scale automated-agent systems, Artificial Intelligence Journal, 110(1):1-55, 1999. for a short paper on flocking behaviors and how "By tapping into social cues, individuals in a group may gain access to higher-order computational capacities that mirror the group's responses to its environment." read I. Couzin (2007). Collective Minds Nature, Vol 445, p. 715.
Day 4: Mon Mar 10 Afternoon	Coordination and Bargaining/Negotiation Required reading:
13:00-14:00	Jeffrey S. Rosenschein and Gilad Zlotkin, Designing Conventions for Automated Negotiation, AI Magazine, 15(3): Fall 1994, 29-46
	Inon Zuckerman, Sarit Kraus, and Jeffrey S. Rosenschein. Using Focal Point Learning to Improve Tactic Coordination in Human-Machine Interactions, IJCAI 2007, Hyderabad, India, January 2007, pages 1563-1568.
14:00-17:00	Guest lecture by Catholijn Jonker
	Koen Hindriks, Catholijn Jonker and Dmytro Tykhonov, Negotiation Dynamics: Analysis, Concession Tactics, and Outcomes", IAT'07, ISBN 0-7695-3027-3, IEEE/WIC/ACM international conference on intelligent agent technology, pp. 427-433, 2007
	Koen Hindriks, Catholijn Jonker and Dmytro Tykhonov, Analysis of Negotiation Dynamics, CIA'07, ISBN 3-540-75118-1, LNAI, no. 4676, pp. 27-35, Springer, 2007.
15:00-17:00	Computer lab session led by Catholijn Jonker
Speakers
13:00-14:00	Mi Zhang - Lecture slides on paper 1 and 2
14:00-17:00	Catholijn Jonker
15:00-17:00	Computer Lab: Everybody Additional material on Coordination and Negotiation: an earlier paper on negotiation which has received the Influential Paper Award for 2007: J. S. Rosenschein and M. R. Genesereth, "Deals Among Rational Agents" 9th IJCAI, Los Angeles, Ca, August 1985, pages 91-99. an earlier paper on focal points: M. Fenster, S. Kraus and J. Rosenschein. Coordination without Communication: Experimental Validation of Focal Point Techniques, 1st Int'l Conf on Multiagent Systems, pp 102--108, June 1995, Ca, USA. and a much longer paper on focal points: S. Kraus, J. S. Rosenschein and M. Fenster Exploiting Focal Points Among Alternative Solutions: Two Approaches, Annals of Mathematics and Artificial Intelligence, 28(1-4):187-258, 2000. Additional material to the talk by Catholijn Jonker: P. Faratin, C. Sierra, and N. Jennings, Using Similarity Criteria to Make Negotiation Trade-Offs, Journal of Artificial Intelligence, 142 (2), 2003, pp. 205-237. Koen Hindriks and Dmytro Tykhonov, "Opponent Modelling in Automated Multi-Issue Negotiation", AAMAS'08, 2008.
Day 5: Tue Mar 11 Morning	Project and Proposal Presentations Required reading:
9:00-9:40	Carsten Block -- Proposal
9:40-10:20	Timothy Broesamle -- Proposal
10:40-11:20	Rui de Almeida -- Proposal
11:20-12:00	Milan Lovic -- Proposal
Day 5: Tue Mar 11 Afternoon	Project and Proposal Presentations Required reading:
13:20-14:00	Wolf Ketter
14:00-14:40	Annie Yang -- Proposal
14:40-15:20	Mi Zhang -- Proposal
15:20-16:00	Jordan Srour -- Proposal
16:00-17:00	Wolf Ketter -- Workshop wrap-up