M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Journal of Electronic Transactions of Artificial Intelligence, May 2001.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....to consider the context in which the services evolve. In this paper, we present our software agent based approach that implements such a solution. Our approach takes advantage of the research done in Distributed Artificial Intelligence (DAI) 3] in general and the planning field in particular [9]. In a dynamic environment, it is recommended to decompose the planning process into several steps, each step to take care of a portion of the plan that is under development. When a portion of the plan is finished, it is immediately submitted for execution. When the execution of that portion is ....

M. Paolucci, O. Shehory, and K. Sycara. Interleaving Planning and Execution in a Multiagent Team Planning Environment. Technical report, CMU-RI-TR-00-01 The Robotics Institute, Carnegie Mellon Univeristy, Pittsburgh, USA, 2000.

....une architecture qui n utilise pas de m6diateur, alors que InfoSleuth et UMDL utilisent un mddiateur. Dans ce qui suit, nous allons prdsenter l une et l autre forme de ces deux d architectures en les comparant h NetSA. 5. 1 Architectures sans mdiateur: I exemple de Ret sina Les auteurs de Retsina [26, 22] ont d6velopp6 un ensemble d agents logiciels coop6rants de manibm asynchrone pour la qute d information et pour l int6gration de prises de d6cisions vari6es, telles que l aide h la d6cision dans les organisations, la gestion de porte feuille d actions, etc. Comme toute architecture multiagent, ....

M. Paolucci, O. Sheory et K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Electronic Transactions of Artificial Intelligence, (h venir), 2001.

....(planning agents) or from its own experience. travel by train train2 trst0 trst2 travel by airplane airplane0 airport0 airport2 Fig. 6 Operators that will be translated into queries. Other authors build agents (or systems) that are able to interleave planning with execution of actions (Paolucci and Shehory and Sycara 2000). This ability is used to construct shared plans with other agents and to manage the negotiation process, or is used to extend classical planner representations and algorithms to deal with incomplete information, like in XII planner (Golden and Etzioni and Weld 1996) Golden and Weld 1996) We ....

M. Paolucci, O. Shehory, and K. Sycara. "Interleaving Planning and Execution in a Multiagent Team Planning Environment". tech. report CMU-RI-TR-00-01, Robotics Institute, Carnegie Mellon University, January, 2000.

....agents. However, much work is still needed in developing well founded reasoning and negotiating techniques, in particular in environments in which the agent must constantly be on the lookout for changes (see [dDJW99] for a recent survey) An interesting approach is the RETSINA project [PKP ng,PSS00] In RETSINA each agent can do its own planning, as each agent is equipped with a special planning component in its internal architecture. In contrast to this, we have chosen that one special planning agent, shop, does the planning upon request from other agents. Dix, Mu noz Avila, Nau ....

M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent teamplanning environment. In CMU-RI-TR-00-01, 2000.

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M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Journal of Electronic Transactions of Artificial Intelligence, May 2001.

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M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Journal of Electronic Transactions of Artificial Intelligence, May 2001.

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M. Paolucci, O. Shehory, and K. Sycara, "Interleaving planning and execution in a multiagent team planning environment," Journal of Electronic Transactions of Artificial Intelligence, May 2001.

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M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Journal of Electronic Transactions of Artificial Intelligence, May 2001.

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M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Journal of Electronic Transactions of Artificial Intelligence, May 2001.

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M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Technical Report CMU-RI-TR-00-01, The Robotics Institute, Carnegie Mellon University, 2000.

....functionally, we believe that it is possible to uniformly de ne agent behaviors [4] that are consistent with their functional description. The RETSINA Individual Agent Architecture [23, 4] is illustrated by Figure 2. This agent architecture implements Hierarchical Task Network (HTN) Planning [7, 15] in three parallel execution threads. A fourth thread, the Communicator [19] provides the means by which the agent communicates with the networked world. The coordination among the three planning modules is done in such a way that highpriority actions can interrupt those being executed by the ....

M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Technical report, CMU, 2000.

....from their operating environment during execution time. The acquisition and maintenance of the contextual information that determines the plan requirements is performed by NaCoDAE, a conversational case based reasoner, which is used to compositionally generate Hierarchical Task Network [HTN] plan[10,19] objectives for the RETSINA team agents. We show that the unobtrusive and invisible use of NaCoDAE as the primary means by which human and agent information is gathered and merged can eliminate any information overload that might result from the conscious interactions of humans with their ....

....concurrent threads and the arrows represent control and data flow. The external entities may be agent or non agent software components. The RETSINA Individual Agent Architecture[27, 4, 7] is illustrated by Figure 2. This agent architecture implements Hierarchical Task Network [HTN] Planning [10,19] in three parallel execution threads. A fourth thread, the Communicator [23] provides the means by which the agent communicates with the networked world. The Communicator provides a level of abstraction that insulates the planning component from issues of agent communication language [ACL] ....

M. Paolucci, O. Shehory, and K. Sycara. Interleaving planning and execution in a multiagent team planning environment. Technical Report CMU-RI-TR-00-01.

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M. Paolucci, O. Shehory, and K. Sycara, Interleaving Planning and Execution in a Multiagent Team Planning Environment, tech. report CMU-RI-TR-00-01, Robotics Institute, Carnegie Mellon University, January, 2000.

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M. Paolucci, O. Shehory, K. Sycara, Interleaving Planning and Execution in a MultiagentTeam PlanningEnvironment, Technical report, CMU-RI-TR-00-01, The Robotics Institute, Carnegie Mellon University, Pittsburgh, USA, 2000.

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Paolucci, M., Shehory, O., Sycara,K.: Interleaving planning and execution in a multiagent team planning environment. Electronic Transactions of Artificial Intelligence, (2001)

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