@article{nourbakhsh05, author = "Illah Nourbakhsh and Katia Sycara and Mary Koes and Mark Yong and Michael Lewis and Steve Burion", title = "Human-Robot Teaming for Search and Rescue", journal = "IEEE Pervasive Computing: Mobile and Ubiquitous Systems", month = "January", year = "2005", pages = "72-78" } @inproceedings{ladcop1, author = "Paul Scerri and A. Farinelli and S. Okamoto and M. Tambe", title = "Allocating Tasks in Extreme Teams", booktitle = "Proc. of the fourth international joint conference on Autonomous agents and multiagent systems", year = "2005" } @inproceedings{ schneider05, author="Jeff Schneider and David Apfelbaum and Drew Bagnell and Reid Simmons", title="{Learning Opportunity Costs in Multi-Robot Market Based Planners}", booktitle = "Proc. of the IEEE Intl. Conf. on Robotics and Automation (ICRA)", year = 2005, } @phdthesis{bererton, author = "Curt Bererton", title = "Multi-Robot Coordination and Competition Using Mixed Integer and Linear Programs", school = "Robotics Institute, Carnegie Mellon University", month = "August", year = "2004", address = "Pittsburgh, PA" } @inproceedings{adopt, author = {Pragnesh Jay Modi and Wei-Min Shen and Milind Tambe and Makoto Yokoo}, title = {An asynchronous complete method for distributed constraint optimization}, booktitle = {Proc. of the second international joint conference on Autonomous agents and multiagent systems}, year = {2003}, pages = {161--168}, location = {Melbourne, Australia}, OPTpublisher = {ACM Press}, } @inproceedings{maheswaran04, author = {Rajiv T. Maheswaran and Milind Tambe and Emma Bowring and Jonathan P. Pearce and Pradeep Varakantham}, title = {Taking {DCOP} to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling}, booktitle = {Proc. of the Third International Joint Conference on Autonomous Agents and Multiagent Systems}, year = {2004}, pages = {310--317}, location = {New York, New York}, } @article{sandholm97, author = "Tuomas Sandholm and Victor Lesser", title = "{Coalitions Among Computationally Bounded Agents}", journal = "Artificial Intelligence, Special Issue on Economic Principles of Multi-Agent Systems", volume = "94", number = "1", pages = "99-137", month = "January", year = "1997", } @article{shehory98, author = "Onn Shehory and Sarit Kraus", title = "Methods for task allocation via agent coalition formation", journal = "Artificial Intelligence", month = "May", year = "1998", volume = "101", number = "1-2", pages = "165-200" } @techreport{li03, author = "Cuihong Li and Shuchi Chawla and Uday Rajan and Katia Sycara", title = "Mechanisms for Coalition Formation and Cost Sharing in an Electronic Marketplace", institution = "Robotics Institute, Carnegie Mellon University", month = "April", year = "2003", number = "CMU-RI-TR-03-10", address = "Pittsburgh, PA" } @InProceedings{gerkey04ss, author = "B. Gerkey and M. Mataric", title = "Are (explicit) multi-robot coordination and multi-agent coordination really so different?", booktitle = "Proceedings of the AAAI Spring Symposium on Bridging the Multi-Agent and Multi-Robotic Research Gap", pages = "1--3", address = "Palo Alto, California", month = "March", year = "2004", url = "http://robotics.stanford.edu/~gerkey/research/final_papers/aaaiss04.pdf" } @article{ gerkeymataric02, author = "B. Gerkey and Maja Matari\'{c}", title = "Sold!: Auction methods for multi-robot coordination", journal = "{IEEE} Transactions on Robotics and Automation, Special Issue on Multi-robot Systems", volume = "18(5)", pages = "758--768", month = "October", year = "2002"} @inproceedings{ jonesmataric04, author="Chris Jones and Dylan Shell and Maja J Matari\'{c} and Brian Gerkey", title="Principled Approaches to the Design of Multi-Robot Systems", booktitle = "Proc. of the Workshop on Networked Robotics, {IEEE}/{RSJ} International Conference on Intelligent Robots and Systems ({IROS} 2004)", address = "Sendai, Japan", month = "September", year = "2004"} @inproceedings{ gerkeymataric03a, author="Brian P. Gerkey and Maja J Matari\'{c}", title="{Multi-Robot Task Allocation: Analyzing the Complexity and Optimality of Key Architectures}", booktitle = "Proc. of the IEEE Intl. Conf. on Robotics and Automation", year = 2003, address = "Taipei, Taiwan", month = "May", url = "citeseer.ist.psu.edu/gerkey02multirobot.html" } @article{ dudek96taxonomy, author = "G. Dudek and M. Jenkin and E. Milios and D. Wilkes", title = "A taxonomy for multi-agent robotics", journal = "Autonomous Robots", volume = "3", pages = "375--397", year = "1996", url = "citeseer.ist.psu.edu/article/dudek96taxonomy.html" } @InProceedings{ parker00current, author = {L. E. Parker}, title = "Current State of the Art in Distributed Autonomous Mobile Robotics", booktitle = "Distributed Autonomous Robotic Systems 4", editor = "L. E. Parker and G. Bekey and J. Barhen", publisher = "Springer-Verlag Tokyo", pages = "pp. 3--12", year = "2000" } @article{ Jennings97, author = "N. R. Jennings and J. R. Campos", title = "Towards a Social Level Characterisation of Socially Responsible Agents", journal = "IEE Proceedings on Software Engineering", volume = "144", number = "1", pages = "11--25", year = "1997", } @article{ desjardins99survey, author = "M. desJardins and E. Durfee and C. Ortiz and M. Wolverton", title = "A survey of research in distributed, continual planning", journal = "AI Magazine", volume = "4", pages = "13-- 22", year = "1999", url = "citeseer.ist.psu.edu/desjardins00survey.html" } @InProceedings{Scerri04, author = {P. Scerri and Y. Xu and E. Liao and J. Lai and K. Sycara}, title = {Scaling Teamwork to Very Large Teams}, booktitle = {{AAMAS}'04}, OPTcrossref = {}, OPTkey = {}, OPTpages = {}, year = {2004}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, address = {New York, NY}, month = {July}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {}, OPTannote = {} } @TechReport{Lerman2001, author = {K. Lerman and A. Galstyan}, title = {A General Methodology for Mathematical Analysis of Multi-Agent Systems}, institution = {USC Information Sciences}, year = {2003}, OPTkey = {}, type = {Technical Report {ISI}-{TR}-529}, OPTnumber = {}, } @TechReport{TraderBots03, author = {M. Dias and A. Stentz}, title = {TraderBots: A Market-Based Approach for Resource, Role, and Task Allocation in Multirobot Coordination}, institution = {Robotics Institute, Carnegie Mellon University}, year = {2003}, type = {{CMU}-{RI}-{TR}-03-19}, address = {Pittsburgh, {PA}}, month = {August}, } @Proceedings{Boman98, author = {M. Boman and H. Verhagen}, title = {Social Intelligence as Norm Adaptation}, year = {1998}, OPTkey = {}, OPTeditor = {B. Edmonds and K. Dautenhahn}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, month = {August}, organization = {Socially Situated Intelligence: a workshop held at {SAB}'98}, OPTpublisher = {}, OPTnote = {}, OPTannote = {} } @article{ Dignum99, author = "Frank Dignum", title = "Autonomous Agents with Norms", journal = "Artificial Intelligence and Law", volume = "7", number = "1", pages = "69-79", year = "1999" } @inproceedings{ Sierra97, author = "C. Sierra and P. Faratin and N. Jennings", title = "A Service-Oriented Negotiation Model between Autonomous Agents", booktitle = "Proceedings of the 8th European Workshop on Modeling Autonomous Agents in a Multi-Agent World ({MAAMAW}-97)", address = "Ronneby, Sweden", pages = "17--35", year = "1997" } @inproceedings{Dias04, author = "M Bernardine Dias and Robert Michael Zlot and Marc B Zinck and Juan Pablo Gonzalez and Anthony (Tony) Stentz", title = "A Versatile Implementation of the TraderBots Approach for Multirobot Coordination", booktitle = "International Conference on Intelligent Autonomous Systems ({IAS}-8)", month = "March", year = "2004" } @article{Doran97, author = "J. E. Doran and S. Franklin and N. R. Jennings and T. J. Norman", title = "On Cooperation in Multi-Agent Systems", journal = "The Knowledge Engineering Review", volume = "12", number = "3", pages = "309--314", year = "1997" } @inproceedings{ NIST, author = "A. Jacoff and E. Messina and J. Evans", title = "Experiences in Deploying Test Arenas for Autonomous Mobile Robots", booktitle = "Proc. 2001 Performance Metrics for Intelligent Systems Workshop (PerMIS01)", address = "National Inst. of Standards and Technologies", year = "2002" } @Misc{altruisticgames, OPTkey = {}, author = {E. Camponogara}, title = {Altruistic Agents in Dynamic Games}, howpublished = {Proc. 16th Brazilian Symposium on Artificial Intelligence, Lecture Notes in Artificial Intelligence}, pages = {74-84}, month = {November}, year = {2002}, OPTnote = {}, OPTannote = {} } @article{floyd, author = "Robert W. Floyd", title = "Algorithm 97 ({SHORTEST PATH})", journal = cacm, volume = 5, number = 6, year = 1962, pages = 345, mon = jun } @InProceedings{Mataric92, author = {M. Mataric}, title = {Designing emergent behaviors: From local interactions to collective intelligence}, booktitle = {In Proceedings of the International Conference on Simulation of Adaptive Behavior: From Animals to Animats}, OPTcrossref = {}, OPTkey = {}, OPTpages = {}, OPTyear = {}, OPTeditor = {}, volume = {2}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {}, OPTannote = {}, pages = {432-441}, year = {1992} } @inproceedings{ Balch99, author = "T. Balch and R. Arkin", title = "Behavior-based Formation Control for Multi-robot Teams", booktitle = "{IEEE} Transactions on Robotics and Automation", year = "1999" } @incollection{Vail03, author = "Douglas Vail and Maria Manuela Veloso", editor = "A. Schultz and L. Parker and F. Schneider", title = "Multi-Robot Dynamic Role Assignment and Coordination Through Shared Potential Fields", booktitle = "Multi-Robot Systems", publisher = "Kluwer", year = "2003" } @inproceedings{ adelsberger00economic, author = "Heimo H. Adelsberger and Wolfram Conen", title = "Economic Coordination Mechanisms for Holonic Multi Agent Systems", booktitle = "{DEXA} Workshop", pages = "236-240", year = "2000" } @inproceedings{Dias04_2, author = "M Bernardine Dias and Marc B Zinck and Robert Michael Zlot and Anthony (Tony) Stentz", title = "Robust Multirobot Coordination in Dynamic Environments", booktitle = "IEEE International Conference on Robotics and Automation (ICRA)", month = "April", year = "2004" } @InProceedings{Zlot03, author = {R. Zlot and A. Stentz}, title = {Multirobot Control Using Task Abstraction In a Market Framework}, booktitle = {Collaborative Technology Alliances Conference}, OPTcrossref = {}, OPTkey = {}, OPTpages = {}, year = {2003}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {}, OPTannote = {} } @Article{Jennings98, author = {N. Jennings and K. Sycara and M. Wooldridge}, title = {A Roadmap of Agent Research and Development}, journal = {Journal of Autonomous Agents and Multi-agent Systems}, year = {1998}, OPTkey = {Autonomous agents, multi-agent systems, history, teamwork, self interested agents}, volume = {1}, OPTnumber = {}, pages = {7 -- 38}, OPTmonth = {}, OPTnote = {This paper provides an overview of agent research and development in multi-agent systems. It provides some history, but mostly focuses on issues in the field. It defines the three most important characteristics of an agent as situatedness, autonomy, and flexibility. It discusses teamwork versus self interested agents, communication problems, various applications for agents, and various hurtles to overcome in the future. }, OPTannote = { The goal of the paper is to provide an overview, standardize some terminology, and point the reader to other sources for further investigation. The paper really didn't provide too many unique ideas, most giving an overview of other work. The definitions and insights seem okay. It's a nice overview paper, if a little bit out of date. I took away from this paper the idea that working as a team is more difficult but the way to go. } } @Article{Tambe97, author = {M. Tambe}, title = {Towards Flexible Teamwork}, journal = {Journal of Artificial Intelligence Research}, year = {1997}, OPTkey = {Teamwork, multi-agent systems}, volume = {7}, OPTnumber = {}, pages = {83 -- 124}, OPTmonth = {}, OPTnote = {The paper identifies a shortcoming of teamwork in the current multi-agent systems in replanning in the cases of failure or the arrival of an unexpected opportunity as well as the high dependency on the domain. The central hypothesis is that providing agents with a general model of teamwork enables them to address these difficulties. The author presents their model, based on joint intensions and SharedPlan, which they have implemented and call STEAM (Shell for TEAMwork). They apply their system to travel in a convoy, attacking, and Robocup soccer. It also addresses the importance of efficient communication using a decision theoretic framework to reason about communication, showing a correlation between collaboration and communication.}, OPTannote = {This is a good overview of teamwork in 1997. It's a little out of date and so it's analysis of the systems of the time are not so useful. It's discussion of joint intentions and SharedPlan, however, is nice and easy to understand. Their scale was limited by computing power in 1997 as all the simulations were performed on a single computer. It is unclear how it would scale, though the principles seem sound. One shortfall of the approach is that the team strategies are static for a given configuration. There is no learning permitted, though this shortfall may be addressed in subsequent papers. The work also does not deal with unreliable communication. } } @Article{Sycara96, author = {K. Sycara and K. Decker and A. Pannu and M. Williamson and D. Zeng}, title = {Distributed Intelligent Agents}, journal = {IEEE Expert}, year = {1996}, OPTkey = {Multi-agent systems, {RETSINA}}, OPTvolume = {}, OPTnumber = {}, OPTpages = {}, month = {December}, OPTnote = {This paper presents the {RETSINA} (Reusable Task Structure-based Intelligent Network Agents). It explains that {RETSINA} has 3 types of agents: Interface agents: interact with the user, receive user specifications and deliver results Task agents: formulate problem solving plans and carry out these plans by communicating with other agents Information agents: provide intelligent access to a heterogeneous collection of information sources The paper presents the need for a distributed system rather than a centralized system. It presents characteristics for a good agent (taskable, network-centric, semi-autonomous, persistent, trustworthy, anticipatory, active, collaborative, able to deal with different agents, and adaptive), describes the key criteria for a good MAS architecture, and describes several applications }, OPTannote = {It's RETSINA. Nuff said.} } @InBook{Sandholm99, author = {T. Sandholm}, editor = {G. Weiss}, title = {Multi-agent Systems: A Modern Introduction to Distributed Artificial Intelligence}, chapter = {Distributed Rational Decision Making}, publisher = {{MIT} Press}, year = {1999}, OPTkey = {overview, interaction protocols, self interested agents, stability}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTtype = {}, OPTaddress = {}, OPTedition = {}, OPTmonth = {}, pages = {201 -- 258}, OPTnote = {This paper gives an introduction to various interaction protocols for self interested agents including voting, auctions, bargaining, markets, contracting, and coalition formation. It describes each in terms of various criteria including social welfare, pareto efficiency, individual rationality (IR), and stability}, OPTannote = {This is a relatively easy to read introduction to the subjects mentioned above. It is, however, a chapter to a book, rather than a research paper, and so does not extensively discuss how this theory can be applied in research. It is useful background information but not so useful for collaborative robotics and teamwork where the robots are not self interested but are working as a team. Also, as we can design the strategy for each robot, designing protocols to be non-manipulable is not necessary.} } @Article{Nwana96, author = {H. Nwana and L. Lee and N. Jennings}, title = {Coordination in Software Agent Systems}, journal = {BT Technology Journal}, year = {1996}, OPTkey = {Coordination, multi-agent systems, overview}, volume = {14}, number = {4}, pages = {79 -- 88}, OPTmonth = {}, OPTnote = {This paper provides an introduction to cooperation, coordination, and communication in multi-agent systems and then goes on to describe four methods for coordination and critique each one: Organizational structuring,Contracting: contract net framework, Multi-agent Planning, Negotiation }, OPTannote = {This paper is meant to be an overview of various techniques. I think it is pretty dated. For example, I'm pretty sure that the game theory negotiation has progressed to the point that we don't have to make the assumptions the author points out. I'm not sure I agree with all the definitions of coordination and cooperation they provide. Overall, I think Jennings 98 paper is a much better overview.} } @InBook{Jennings96, author = {N. Jennings}, OPTALTeditor = {}, title = {Foundations of Distributed Artificial Intelligence}, chapter = {Coordination Techniques for Distributed Artificial Intelligence}, publisher = {Wiley}, year = {1996}, OPTkey = {Distributed Artificial Intelligence (DAI), commitments, conventions, coordination}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTtype = {}, OPTaddress = {}, OPTedition = {}, OPTmonth = {}, pages = {187 -- 210}, OPTnote = {The paper defines coordination (the process by which an agent reasons about its local actions and the (anticipated) actions of others to try to ensure the community acts in a coherent manner), provides reasons for using coordination (dependencies between agents actions, global constraints/shared resources, or no individual can complete problem alone), and discusses commitments and conventions as a means to achieve coordination. The paper identifies a tradeoff between the ability to handle uncertain environments and the amount of time spent acting rather than planning which governs how frequently commitments need to be reevaluated. The paper modifies a statement by Durfee in 1989 to say that there are 4 ingredients for coordination: commitments, conventions, social conventions, and local reasoning. The definitions bear repeating: COORDINATION requires: Commitments: pledges to undertake a specific course of action. Commitments mean that an agent will perform an action providing that its circumstances do not change. How often commitments are reevaluated leads to conventions Conventions: means of monitoring commitments in changing circumstances, specifically how an individual agent should monitor its commitments. They do not say how an agent should behave towards its fellow community members if it alters or modifies its commitments. For this, we have social conventions. Social conventions: specify how an agent should behave with respect to the other community members when its commitments alter. These conventions are hard to design, requiring a balance between propagating useful information to the community as quickly as possible and avoiding bogging down the communication lines and distracting other agents. Local reasoning: the agents must have sufficient knowledge and reasoning capability to exploit the available structure and flexibilty. The paper claims that all coordination mechanisms can be expressed using these concepts, showing that the three most common coordination techniques can be reformulated in these terms. }, OPTannote = {While the paper does a good job of explaining commitments, conventions, and social conventions, it ignores much of the practicality of these ideas. It is nice to know that coordination can be viewed in terms of commitments and conventions but this is such a broad statement that it provides little practical help. Although several sample conventions are provided, there is no evidence that the authors implemented these conventions or what their results were. For a theory paper, the proof is remarkably lax, though the statement isn't (in my mind) all that exciting anyway. However, it is a good overview paper on commitments and conventions} } @Article{Jennings93, author = {N. Jennings}, title = {Commitments and Conventions: The Foundation of Coordination in Multi-Agent Systems}, journal = {Knowledge Engineering Review}, year = {1993}, OPTkey = {Distributed Artificial Intelligence ({DAI}), commitments, conventions, coordination}, volume = {8}, number = {3}, pages = {223 -- 250}, OPTmonth = {}, OPTnote = {Commitments: pledges to undertake a specific course of action. Commitments mean that an agent will perform an action providing that its circumstances do not change. How often commitments are reevaluated leads to conventions. Conventions: means of monitoring commitments in changing circumstances, specifically how an individual agent should monitor its commitments. Several other coordination techniques that do not explicitly involve commitments and conventions are reformulated in these terms to support the paper. }, OPTannote = {This paper is like a rough draft of his 96 paper} } @Misc{Grosz96, OPTkey = {Collaboration, Agents}, author = {B. Grosz}, title = {Collaborative Systems}, howpublished = {AAAI-94 Presidential Address, reprinted}, OPTmonth = {}, year = {1996}, OPTnote = {This paper introduces collaboration in multi-agent systems, provides motivation for collaboration, introduces the "intending-that" attitude central to SharedPlan model for teamwork, discusses the SharedPlan model informally, compares it to Bratman's model for collaboration, and discusses agent characteristics, negotiation, and intention-conflict resolution. It identifies the following areas as open research problems: Plan construction Multi-agent learning Agent-action assignment Modeling commitment Communication requirements, constraints, and tradeoffs Negotiation Intention-Conflict resolution }, OPTannote = {This seems to be a well thought out paper/speech. The issues raised in 1994 are still problems today, though progress is being made. I appreciated this overview to the SharedPlan model of teamwork as it finally sort of makes sense now} } @InProceedings{Eriksson99, author = {J. Eriksson and N. Finne and S. Janson}, title = {{SICS} MarketSpace--An Agent-Based Market Infrastructure}, booktitle = {Proceedings of the 1998 Workshop on Agent-Mediated Electronic Trading}, OPTcrossref = {}, OPTkey = {market, agent, infrastructure}, OPTpages = {}, year = {1999}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {The paper presents their own system, SICS MarketSpace, which they have developed. They also present their own language for the system, market interaction language, which is similar to KQML but more specific to their system. They also present Market Interest Format (MIF) for encoding the interests of the user of the system}, OPTannote = {Yet another multi-agent system...the downsides are that they've developed their own language and format rather than using a quasi-standard one. They identify as an area for future work being open to other languages, so maybe they've since implemented this, but it seems to me to be another domain specific system. It seems like their system should work relatively well for their domain but is not very portable to other domains. Not nearly as powerful as RETSINA} } @Article{Durfee95, author = {E. Durfee and V. Lessing and D. Corkill}, title = {Trends in Cooperative Distributed Problem Solving}, journal = {Transactions on Knowledge and Data Engineering}, year = {1989}, OPTkey = {Cooperative Distributed Problem Solving (CDPS)}, volume = {1}, number = {1}, pages = {63 -- 83}, OPTmonth = {}, OPTnote = {This (relatively old) paper describes CDPS: its benefits, some sample applications (most of which have since been implemented), and some approaches (negotiation, Functionally-Accurate Cooperation, Organizational Structuring, Multi-Agent Planning, Sophisticated Local Control, and Theoretical Frameworks). Negotiation takes a top down view of problem solving while FA/C takes a bottom up view. }, OPTannote = {While probably visionary in 1989, this paper is somewhat dated and more recent papers do a better job of explaining current trends and approaches. Still, it's kind of interesting to see how thoughts have evolved over time.} } @InProceedings{Das02, author = {S. Das and B. Grosz and A. Pfeffer}, title = {Learning and Decision-Making for Intention Reconciliation}, booktitle = {Proceedingsof the First Joint Conference on Autonomous Agents and Multi-Agent Systems}, OPTcrossref = {}, OPTkey = {Evolution, adaptation, learning, group and organizational dynamics, SPIRE (SharedPlans Intention Reconciliation Experiments), DAI}, OPTpages = {}, year = {2002}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, month = {July}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {Since agents cannot make conflicting commitments, they must decide what to do in this case, or reconcile these intentions. Within the SPIRE simulation system, agents have reputations, which are hurt when they do not honor a commitment, and reputations can only be repaired over time. In the tests, the agents may decide whether or not to default on a commitment, based on a cutoff value. They also apply machine learning techniques to improve performance of the multi-agent system and provide experimental results.}, OPTannote = {This is the first paper I've read that actually explained the SPIRE model. It seems really interesting. I like the idea of reputations. It's sort of similar to the eBay system where users get feedback and some people won't accept commitments from people with negative ratings. I don't like the cutoff value in their model for intention reconciliation. Thresholds are just too arbitrary, unless they can actually be theoretically calculated, rather than experimentally determined. Even applying machine learning seems a sort of inelegant way to attack the problem, though I can't think of any better alternatives. } } @InProceedings{Cohen95, author = {P. Cohen and H. Levesque}, title = {Communicative Actions for Artificial Agents}, booktitle = {Proceedings of the First International Conference on Multi-Agent Systems ({ICMAS} '95)}, OPTcrossref = {}, OPTkey = {Agent Communication Languages (ACL), KQML, speech acts}, pages = {65 -- 72}, year = {1995}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {This paper discusses the semantics of KQML as it applies to agent communication. It identifies some difficulties with KQML and some ways to overcome these difficulties. It claims that an ACL should have the following capabilities: allow agents to request and provide support to other agents, allow commitments to be accepted or declined, allow the monitoring of commitments, progress reports, and make acknowledgements. KQML is based on speech act theory. Agents communicate using performatives. However, the performatives in KQML are poorly defined and their exact meaning is unclear. In general, it claims that there are 3 difficulties with KQML: ambiguity and vagueness, misidentified performatives, and missing performatives. It proposes remedies for KQML, at least for use as an ACL.}, OPTannote = {It is interesting to see that KQML was objectively evaluated as an agent communication language. There is a lot more theory in here than I would have expected, though I'm not sure I followed it all in this paper. I assume that the objections to KQML have been addressed since 1995 since it seems to be a widely used ACL. } } @InProceedings{Guerin00, author = {F. Guerin and J. Pitt}, title = {A Semantic Framework for Specifying Agent Communication languages}, booktitle = {Proceedings of the Fourth International Conference on Multi-Agent Systems ({ICMAS}-2000)}, OPTcrossref = {}, OPTkey = {Agent Communication Languages (ACL)}, pages = {395 -- 396}, year = {2000}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, organization = {{IEEE} Computer Society}, OPTpublisher = {}, OPTnote = {This paper breaks current ACLs into two categories: protocol based semantics and intentional semantics. It then proposes a hybrid ACL and evaluates the proposed ACL.}, OPTannote = {This is more advanced than we would need for the USAR domain as it is designed to allow agents to be deceiptful. Our agents are benevolent and truthful so it is not clear that this new ACL would be better than existing ACLs. Also, I'm still not sure I understand the difference between protocol based semantics and intentional semantics.} } @InProceedings{Bigham98, author = {J. Bigham and A. L. G. Hayzelden}, title = {Subsumption and survivability in bidding for bandwidth}, booktitle = {Proceedings of the International Conference on Multi Agent Systems ({ICMAS} '98)}, OPTcrossref = {}, OPTkey = {Survivability, auction}, OPTpages = {}, year = {1998}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {A telecommunications application is used to show how agents in a hybrid subsumption architecture can interact to create the applied policy. It is argued that in a subsumption approach the utility measure of a level of competence should be augmented by a measure of 'survivability'. It is also shown that the process of finding the best flow in the network can be viewed as an auction where the prices are obtained form the derivatives of the survivability function. In the application a simple measure of survivability maps into familiar routing heuristics. More complete measures of survivability give new and potentially useful heuristics}, OPTannote = {The only interesting thing is this paper is the idea of surprises being a problem because the time lag inherent to a system prohibits countering past decisions in sufficient time to react satisfactorily to surprises so even though a policy may be truly optimal with respect to demand at a particular time, it may be better to keep some spare capacity on a resource to deal with surprises} } @InProceedings{Pappachan00, author = {P. M. Pappachan and E. H. Durfee}, title = {Interleaved Plan Coordination and Execution in Dynamic Multi-agent Domains}, booktitle = {Proceedings of the Fourth International Conference on MultiAgent Systems}, OPTcrossref = {}, OPTkey = {Hierarchical Task Networks (HTNs)}, pages = {425 -- 426}, year = {2000}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, month = {July}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {This paper proposes an algorithm that coordinates agents with hierarchical task networks by using a least commitment strategy to incrementally construct a multi-agent plan at runtime. A coordinator maintains a conflict list of operators which can potentially conflict. All operators which are members of this list are blocked. The algorithm interleaves coordination with task execution since operators that are not blocked can be reduced/executed while the coordinator is resolving conflicts. The coordinator does not have to examine entire HTNs before coordinating all the agents. The algorithm does not consider solutions with temporal relations that do not satisfy the reducibility property. The algorithm was implemented and experiments conducted in an evacuation domain in which transport agents have to move evacuees to safe locations along various shared routes that can fail dynamically}, OPTannote = {The algorithm, though potentially interesting, is not fully explained in this brief paper. Because it relies on HTNs, it suffers the same drawbacks of HTNs. Also, it relies on a central coordinator, which is something we want to avoid in multi-agent systems} } @InProceedings{Julian02, author = {V. Julian and V. Botti}, title = {Developing Real-Time Multi-Agent Systems}, booktitle = {Fourth Iberoamerican Workshop on Multi-Agent Systems, Iberagents 2002}, OPTcrossref = {Real-Time, Multi-Agent System, Message, Simba}, OPTkey = {}, OPTpages = {}, year = {2002}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, month = {November}, organization = {{IBERAMIA} 2002, the {VIII} Iberoamerican Conference on Artificial Intelligence}, OPTpublisher = {}, OPTnote = {The application of multi-agent systems to real-time environments is an interesting line of work that can provide new solutions to very complex and restrictive systems such as real-time systems. A suitable method for real-time multi-agent system development must take into account the intrinsic characteristics of systems of this type. This work presents motivation for, definitions of, and an approach for the development of real-time multi-agent systems. The proposed method is called rt-Message and is based on the Message methodology}, OPTannote = {This paper presents for the Message MAS what we want to do with Retsina. However, understanding all their changes requires a deeper understanding of multi-agent systems in general and Message, Simba, and Artis in particular, than I currently possess. They do have some good definitions and insights, however} } @InProceedings{Allouche00, author = {M. Allouche and O. Boisser and C. Sayettat}, title = {Temporal Social Reasoning in Dynamic Multi-Agent Systems}, booktitle = {Proceedings of the Fourth International Conference on Multi-Agent Systems ({ICMAS}-2000)}, OPTcrossref = {}, OPTkey = {Temporal reasoning, Social reasoning, cooperation, dependence relations}, pages = {23 -- 28}, year = {2000}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, organization = {{IEEE} Computer Society}, OPTpublisher = {}, OPTnote = {This paper defines both temporal dependence networks and temporal social reasoning mechanisms for dynamic multi-agent systems. These aspects are then illustrated through an application of supervision of a fleet of buses. Agents must handle time within their individual control mechanisms and their social components. At the individual level, each agent is responsible for a set of tasks that exhibit temporal constraints. This article is more concerned with the social level, where the agent must be aware of the manner to execute her tasks, while remaining coherent with the other agents of the system. Using different existing relations among tasks, agents can compute their dependence networks. They use them as a motivation for cooperation and as a guide for their interactions. This process is called social reasoning. The dynamic dimension is present in the original definition of dependence in the sense that an agent depends on another agent for an action while the former wants this action to be done. In dynamic domains, temporal constraints can be identified among tasks. The paper looks at three different kinds of temporal dependence relations: need, help, and competition. }, OPTannote = {This paper deals more with the high level temporal reasoning, ignoring communication delays and overhead costs that can be significant for a system that must interact in a world where the temporal dependences change significantly in the time it takes for communication. } } @InProceedings{Liu00, author = {R. L. Liu and S. Y. Lin}, title = {Adaptive Coordination of Agents for Timely and Resource-Bounded Information Monitoring}, booktitle = {Fourth International Conference on Multi-Agent Systems}, OPTcrossref = {}, OPTkey = {adaptive agent coordination, resource conflict resolution, timely information monitoring, resource-bounded information monitoring}, OPTpages = {}, year = {2000}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, OPTmonth = {}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {Effective decision-making often relies on timely information monitoring, which aims to capture the newest status of the critical information items that are updated in different ways. This paper presents an adaptive agent coordination strategy ACAIM for directing the limited resources (e.g. loading of related servers and computer networks) to the timely identification of important information updates. ACAIM automatically adapts its coordination strategy by observing each agent's performance of finding important information updates. Resource conflicts among agents are resolved by granting more requests from those agents that are expected to find important information updates. The paper also lists evaluation criteria and experiments to evaluate those coordination strategies designed for timely and resource-bounded information monitoring. The result shows that ACAIM may achieve the more timely identification of important information updates using a controlled amount of system resources. }, OPTannote = {Basically discusses information monitoring of MAS. Presents tradeoff between timeliness and resource consumption (nothing surprising there). This isn't so much an issue for us in USAR since the communication time dominates the timeliness considerations. It is more important for virtual systems. } } @InProceedings{Cardwell00, author = {N. Cardwell and S. Savage and T. Anderson}, title = {Modeling TCP Latency}, booktitle = {Proceedings of {IEEE} {INFOCOM}}, OPTcrossref = {}, OPTkey = {{TCP} Latency}, OPTpages = {}, year = {2000}, OPTeditor = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTaddress = {}, month = {March}, OPTorganization = {}, OPTpublisher = {}, OPTnote = {Corresponded with T. Anderson. He gave me some more references and permission to reprint a figure from their paper}, OPTannote = {} } @Unpublished{Harchol-Balter02, author = {M. Harchol-Balter}, title = {Quality of Service Lectures}, note = {http://www-2.cs.cmu.edu/$\sim$srini/15-441/F02/}, OPTkey = {Networks, latency, bandwidth}, month = {November}, year = {2002}, OPTannote = {} } @InBook{Kurose00, author = {J. F. Kurose and K. W. Ross}, OPTALTeditor = {}, title = {Computer Networking: A Top-Down Approach Featuring the Internet}, chapter = {3.7 TCP Congestion Control}, publisher = {Addison-Wesley}, year = {2000}, OPTkey = {}, OPTvolume = {}, OPTnumber = {}, OPTseries = {}, OPTtype = {}, OPTaddress = {}, OPTedition = {}, month = {July}, OPTpages = {}, OPTnote = {}, OPTannote = {} } @Article{Mussliner95, author = {D. Mussliner and J. Hendler and A. Agrawala and E. Durfee and et al.}, title = {The Challenges of Real-Time AI}, journal = {{IEEE} Computer}, year = {1995}, OPTkey = {}, volume = {28}, number = {1}, pages = {58 -- 66}, month = {January}, OPTnote = {}, OPTannote = {} } @TechReport{Nagle84, author = {J. Nagle}, title = {Congestion Control in {IP/TCP} Internetworks}, institution = {Network Information Center, {SRI} International}, year = {1984}, OPTkey = {}, type = {RFC 896}, OPTnumber = {}, address = {Menlo Park, {CA}}, month = {January}, OPTnote = {}, OPTannote = {} } @Misc{RETSINA03, OPTkey = {}, author = {K. Sycara and M. Paolucci and M. van Velsen and J. Giampapa}, title = {The {RETSINA} {MAS} Infrastructure}, howpublished = {To appear in the special joint issue of Autonomous Agents and MAS}, month = {July}, year = {2003}, OPTnote = {}, OPTannote = {} } @inproceedings{USARpaper, OPTkey = {}, author = {J. Wang and M. Lewis and J. Gennari}, title = {{USAR}: A Game Based Simulation for Teleoperation}, booktitle = {Proc. 47th Ann. Meeting Human Factors and Ergonomics Soc.}, month = {July}, year = {2003}, OPTnote = {}, OPTannote = {} } @book{algorithms, author = {Cormen, Thomas H. and Charles E. Leiserson and Ronald L. Rivest}, title = {Introduction to Algorithms}, publisher = {MIT Press/McGraw-Hill}, year = 1990 }