K. S. Decker and V. R. Lesser. Designing a family of coordination algorithms. Technical Report TR 94-14, Univ. of Massachusetts, Amherst, MA, Aug. 1995.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....robot. Many lessons important for this domain can be learned from the Multi Agent Systems field of Artificial Intelligence (AI) concerning relevant topics for Cooperative Robotics, such as distributed continual planning[5] task allocation[7] communication languages or coordination mechanisms[4]. Robotic soccer is a very challenging problem, where the robots must cooperate not only to push and or kick an object (a ball) towards a target region (the goal) but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles while moving towards, moving with ....

K. S. Decker and V. R. Lesser, "Designing a Family of Coordination Algorithms", Technical Report No. 94-14, Department of Computer Science, University of Massachussets, Amherst, MA01003, 1995

....that guarantee that no event will fail. Just as George , Stuart focuses on the resolution of con icts, and not on potential positive relations between plans. Our framework can also be compared with the PGP (Partial Global Plan) framework described by Durfee et al. 9, 8] and Decker and Lesser ([7]) In this PGP framework and its extension GPGP, agents are allowed to cooperate by exchanging parts of their local plans to develop common plans. The main di erence with our approach to cooperation is that in our framework exchanging parts of local plans is more involved, since exchanging parts ....

Keith S. Decker and Victor R. Lesser. Designing a family of coordination algorithms. In Proceedings of the 13th International Workshop on Distributed Arti cial Intelligence, pages 65-84, Lake Quinalt, Washington, 1994.

....or sub contract them to other agents. When sub contracting, they must pay for having the task executed and therefore shop around for the lowest bidder. Planning Agents that must achieve a common goal have to plan in coordination. An example of coordinate planning is Partial Global Planning (PGP) DL95] where heterogeneous agents can post constraints, or commitments to do a task by some time, to each other local scheduler. Commitment Agents in a society, whether sharing a common goal or self interested, may decide to commit to each other, i.e. agree to pursue a given goal, possibly in a ....

K. S. Decker and V. R. Lesser. Designing a family of coordination algorithms. pages 73-80, Menlo Park, California, June 1995. AAAI Press.

....advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and or a fee. SAC 2002 Madrid, Spain Copyright 2002 ACM 0 58113 445 2 02 03 . 5.00. GPGP) [3] is one of the techniques that provide coordina tion among cooperative agents. It consists of modular coordination mechanisms that use TAEMS model (Task Analysis, Environment Modeling, and Simulation) 2] to reason about the environment. The result of coordination is a set of contrainsts that ....

....Based on TAEMS model five coordination mechanisms were defined. The purpose of these coordination mechanisms is to recogni,e tasks interdependencies and create corresponding commitments and constraints, which in turn is passed to the local scheduler to produce globally better schedules [3, 7]. The first mechanism deals with exchang ing private views in order to construct a more global view. The second mechanism handles simple redundancy where a task s quality is the maximum of its subtasks qualities and these subtasks are also methods. Third mechanism tackles results exchange. ....

K. Decker and V. Lesser. Designing a family of coordination algorithms. In ICMAS, 1995.

....the operation of other agents actions [27] For example, one agent s action can facilitate the actions of other agents, or can enable other agents to perform different activities. The study of these types of non local effects among agents activities is central to coordinate agents in a MAS [9,2]. Not taking into account these relationships can cause multi agent activities to waste resources, perform badly, or even fail [23] On the other hand, agents with information about these relationships can choose their actions exploiting beneficial relationships and avoiding conflicts. ....

....of other actions, either their own actions or actions of another agents. For example, when an agent takes objects from the environment, it inhibits both itself and another agents from doing so. These interactions between tasks being worked on by a single agent are called non local effects [9]. On the other hand, if they occurs between tasks being worked on by different agents, they are called coordination relationships. It is worth noting that a coordination relationship is a special case of a non local effect where two or more agents are involved. Several works have shown that ....

Keith Decker and Victor Lesser. Designing a family of coordination algorithms. In Proceedings of the Thirteenth International Workshop on Distributed AI, pages 65--84, Seattle, WA, July

....constraint programming, where a set of agents or propagators try to reduce a search space to a solution, and where each propagator only sees a small set of variables. 3.3. 2 Generalized PGP The Generalized Partial Global Planning framework by Decker and Lesser also demands cooperative agents [DL95,DL92]. GPGP is a task scheduling framework. It provides a scheduler with a set of rules, called coordination mechanisms , of how it should attribute tasks to agents and in which order they should be executed. The coordination mechanisms are rules used by a central plan controller that can look into ....

Keith S. Decker and Victor R. Lesser. Designing a family of coordination algorithms. In Proceedings of the First International Conference on Multi-Agent Systems, San Francisco, July 1995. ftp://ftp.cs.umass.edu/pub/lesser/decker-94-14.ps.

....numbers IN , and assume that every agent uses the same model, and in addition, that every agent has access to a global system clock. Notice that an alternative approach would be to specify a quality function for each task, which indicates the utility of completing the task at each time point (cf. [3]) The duration of a task indicates the number of time steps required to carry out the task. In order to carry out a task, an agent with the appropriate capability must work on the task for at least this many consecutive time steps in order to complete it. Finally, the priority of a task simply ....

K. Decker and V. Lesser. Designing a family of coordination algorithms. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), pages 73-80, San Francisco, CA, June 1995.

....and computational agents estimate payoff in resource usage and relinquishment to optimize their strategies. Rosenschein and Zlotkin [38] developed a framework on negotiation protocols among agents, where utility metrics define strategies and outcomes in cooperative resource allocation. Decker [4] understands coordination as the act of managing interdependencies between activities and dissects coordination processes into the specifica tion of shared goals, solution planning, and task scheduling, starting with signals for attention, acceptance or refusal of a connection, information ....

K. S. Decker and V. R. Lesser. Designing a family of coordination algorithms. Technical Report TR 94-14, Univ. of Massachusetts, Amherst, MA, Aug. 1995.

....approach is somewhat more general: we assemble the output of an operator by side e ects of a set of other operators such that the rst one becomes obsolete. Our framework can also be compared with the PGP (Partial Global Plan) framework described by Durfee et al. 4,3] and Decker and Lesser ([2]) In this PGP framework and its extension GPGP, agents are allowed to cooperate by exchanging parts of their local plans to develop common plans. The work on plan merging by Ephrati and Rosenschein [5,6,7] shows not only many similarities to our approach, but also some di erences. Through a ....

Keith S. Decker and Victor R. Lesser. Designing a family of coordination algorithms. In Proceedings of the 13th International Workshop on Distributed Articial Intelligence, pages 6584, Lake Quinalt, Washington, 1994.

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K. Decker and V. Lesser. Designing a family of coordination algorithms. In Proceedings of the 1st ICMAS, pages 73--80, San Francisco, June 1995. AAAI Press.

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Decker, K. S. and Lesser, V. R. (1995). Designing a family of coordination algorithms. In Lesser, V. and Gasser, L., editors, Proceedings of the First International Conference on Multi-Agent Systems (ICMAS'95), 12--14 June, San Francisco, CA, pages 73--80, Menlo Park, CA. AAAI Press / MIT Press. (Longer version available as UMass CS-TR 94-14.).

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K. S. Decker and V. R. Lesser. Designing a family of coordination algorithms. In Proceedings of the First International Conference on Multi-Agent Systems(ICMAS-95), San Francisco, 1995.

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K.S. Decker, V.R. Lesser, Designing a family of coordination algorithms, in: Proc. First International Conference on Multi-Agent Systems, San Francisco, CA, AAAI Press, Menlo Park, CA, 1995, pp. 73--80. Longer version available as UMass CS-TR 94--14.

....specific permission and or a fee. AAMAS 02, July 15 19, 2002, Bologna, Italy. Copyright 2002 ACM 1 58113 480 0 02 0007 . 5.00. these embedded coordination mechanisms, each agent is able to learn over time which coordination mechanism is the best for a specific environmental context. Decker [2] and Castelfranchi [3] found that an important way to express coordination mechanisms is to study the relationships of agents goals, the planned tasks to achieve those goals, and required resources. Our work is a general solution to this problem, which is based mainly on two previous ....

....found that an important way to express coordination mechanisms is to study the relationships of agents goals, the planned tasks to achieve those goals, and required resources. Our work is a general solution to this problem, which is based mainly on two previous achievements, TAEMS [4] and GPGP [2]. The key point of GPGP is to assume each agent is capable of reasoning locally about its schedule of activities and possible alternatives. Thus coordination mechanisms of many different styles can be thought of as ways to provide information to a local scheduler that allow it to construct better ....

K. S. Decker and V. R. Lesser. Designing a family of coordination algorithms. ICMAS-95, San Francisco.

....that we think appropriate is to construct coordination mechanisms to handle the dependency relationships among multiple agents tasks. GPGP and TAEMS are the bases of our coordination research. The key point of GPGP (Generalized Partial Global Planning) Both GPGP and TAEMS are explained in [6]) is to assume that each agent is capable of reasoning locally about its schedule of activities and possible alternative schedules. Thus coordination mechanisms can be thought of as ways to provide information to a local scheduler that allows it to construct better schedules. We represent agent ....

K. Decker and V. Lesser. Designing a family of coordination algorithms. International Conference on Multi-Agent Systems, San Francisco, 1995.

....to coordinate there activities to ensure the resource is not over or under loaded[23] Once an agent has detected a point of remote interaction, it can then engage in a process of coordination. The speci cs of such a process are beyond the scope of this article, more details can be found here [21, 5]. More germane is the concept that the agent must both determine what sort of commitment is necessary, and how that can be represented. The example in Figure 15 shows a situation where the success of one action depended on the successful completion of another. Thus a commitment is needed which ....

Keith S. Decker and Victor R. Lesser. Designing a family of coordination algorithms. In Proceedings of the First International Conference on Multi-Agent Systems, pages 73-80, San Francisco, June 1995. AAAI Press.

No context found.

K. S. Decker and V. R. Lesser. Designing a family of coordination algorithms. Technical Report TR 94-14, Univ. of Massachusetts, Amherst, MA, Aug. 1995.

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K. Decker, V. Lesser, Designing a Family of Coordination Algorithms, AAAI Press, 1995, pp. 73--80.

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K.S. Decker and V.R. Lesser. Designing a Family of Coordination Algorithms. In Proceedings of the First International Conference on Multi-Agent Systems. 1995.

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K. S. Decker and V. R. Lesser. Designing a family of coordination algorithms. In Proceedings of The First International Conference on MultiAgent Systems (ICMAS95) , pages 73--80, San Francisco, USA, June 1995.

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K.S. Decker and V.R. Lesser. Designing a Family of Coordination Algorithms. In Proceedings of the First International Conference on Multi-Agent Systems. 1995.

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Decker, K. S., and Lesser, V. R., Designing A Family Of Coordination Algorithms, Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), pp. 73-80, 1995.

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K. Decker and V. Lesser. Designing a family of coordination algorithms. In Proc. of First Int. Conf. on Multi-Agent Systems, pages 73--80, 1995.

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Keith S. Decker and Victor R. Lesser. Designing a family of coordination algorithms. In Proceedings of the Thirteenth International Workshop on Distributed Artificial Intelligence (DAI-94), pages 65--84, 1994.

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K. S. Decker and V. R. Lesser, "Designing a family of coordination algorithms," in M. Huhns and M. P. Singh, (eds.), Readings in Agents, vol. 4.4 Interactive Agency, Morgan Kaufmann Publishers: San Mateo, CA, chapt. 4. Models of Agency, 1997.

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