S. Cammarata, D. MacArthur, and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of The International Joint Conference on Artificial Intelligence, pages 767--770, Karlsruhe, Germany, August 1983.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... used extensively is the contract net protocol [15] 33] other negotiation schemes are described in [18] 21] 32] 39] However, although DAI work has demonstrated success with this approach in a number of domains (e.g. distributed vehicle monitoring [23] and distributed air traffic control [10]) the proposed solutions have not been adequately demonstrated in situated agent (i.e. robotic) teams, which have to live in, and react to, dynamic and uncertain environments amidst noisy sensors and effectors, frequent agent failures, and a limited bandwidth, noisy communication mechanism. The ....

Stephanie Cammarata, David McArthur, and Randall Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of 8th International Joint Conference on Artificial Intelligence, pages 767-770, 1983.

....JRC Ispra, Queen Mary Westfield College, Framentec Cognitech, IRIDIA, Iberdrola, Labein, EA Technology, Amber, National Technical University of Athens (NTUA) University of Amsterdam, Volmac, CERN and University of Porto. G. P. Lekkas was with the NTUA and the JRC Ispra. He is now with Praxis Ltd. 20127 Ispra (VA) Italy. N.M. Avouris was with the JRC Ispra. He is now with the University of Patras, Department of Electrical Engineering, 26500 Rio Patras, Greece. G. K. Papakonstantinou is with the NTUA, Computer Science Division, 15773 Athens, Greece. IEEE Log Number 9406077. used [26] ....

....Queen Mary Westfield College, Framentec Cognitech, IRIDIA, Iberdrola, Labein, EA Technology, Amber, National Technical University of Athens (NTUA) University of Amsterdam, Volmac, CERN and University of Porto. G. P. Lekkas was with the NTUA and the JRC Ispra. He is now with Praxis Ltd. 20127 Ispra (VA) Italy. N.M. Avouris was with the JRC Ispra. He is now with the University of Patras, Department of Electrical Engineering, 26500 Rio Patras, Greece. G. K. Papakonstantinou is with the NTUA, Computer Science Division, 15773 Athens, Greece. IEEE Log Number 9406077. used [26] ....

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S. Cammarata, D. McArthur, and R. Steeb, "Strategies of cooperation in distributed problem solving," in Proc. IJCA1-83, pp. 767-770.

....user interaction features are provided. 3.1 GEOGRAPHICALLY DISTRIBUTED SYSTEMS A traditional area of DAI applications relaters to geographically disu ibuted problems or distributed sensory networks. Examples of applications of this area are the vehicle monitoring domain [30] air traffic control [9], various distributed sensor interpretation systems, the distributed storm forecasting system [21] etc. A common characteristic of these systems at real life scale, especially when wide range geographical distribution is involved and multiple interaction points, is that user interaction occurs at ....

Cammarata, S, McArthur D., and Steeb R. (1983), "Strategies of Cooperation in Distributed Problem Solving," in LICAI83, pp. 767-770.

.... (this agent is called contractor) The negotiation model is proposed in many formulations in literature: the original model (called Contract Net) is developed by Smith and Davis (see [38] 39] 40] 41] 37] other use of negotiation can be found in Conry et al. see [5] Cammarata et al. [4]. c) Centralized Multiagent Planning The model (see [4] has been developed in order to solve conflicts among agents. This approach is based on the identification of a privileged agent elected by all the agents of the system using negotiation. The elected agent forms a multiagent plan that ....

.... is proposed in many formulations in literature: the original model (called Contract Net) is developed by Smith and Davis (see [38] 39] 40] 41] 37] other use of negotiation can be found in Conry et al. see [5] Cammarata et al. 4] c) Centralized Multiagent Planning The model (see [4]) has been developed in order to solve conflicts among agents. This approach is based on the identification of a privileged agent elected by all the agents of the system using negotiation. The elected agent forms a multiagent plan that specifies all agents future actions and interactions. The ....

S. Cammarata, D. McArthur, R. Steeb, "Strategies of cooperation in distributed problem solving", Proceedings of International Joint Conference on Artificial Intelligence, Karlsruhe, Federal Republic of Germany, August

.... agent that has made the best offer (this agent is called contractor) The negotiation paradigm has been proposed in many formulations in literature: the original model (called Contract Net) was developed by Smith and Davis (see [115, 116, 117, 118, 119] other use of negotiation can be found in [24] and [34] Under the general definition of multiagent planning there are several interaction paradigms in which global plans that specify the actions of the agents are built. In this way, there is no conflict among agents. The global plan can be formed in a centralized [24] or in a distributed ....

....can be found in [24] and [34] Under the general definition of multiagent planning there are several interaction paradigms in which global plans that specify the actions of the agents are built. In this way, there is no conflict among agents. The global plan can be formed in a centralized [24] or in a distributed way [36, 60, 82, 84] Eaton et al. 50] propose different interaction paradigms as adequate for different situations: assistance, cooperation, and competition. In particular, when an agent (called the user agent) acquires knowledge from another agent (called the provider ....

S. Cammarata, D. McArthur, and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of International Joint Conference on Artificial Intelligence, pages 767--770, Karlsruhe, Germany, August 1983.

....protocols specified in advance by the system designer. Therefore each agent has little knowledge of the system s overall objective or of general strategies for communication and coordination. In other approaches, the main focus is on coordination strategies between multiple decision makers [15, 32, 34, 37, 78, 79]. Consequently, the mental apparatus and inferential mechanisms of agents are obscured under the mere assumption that agents have their own decision making expertise which frequently has to be coordinated when the goals undertaken by individual agents are related. This definition encapsulates the ....

S. Cammarata, D. McArthur and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of the International Joint Conference On Artificial Intelligence, pp. 767--770, Karlsruhe, 1983.

....knowledge of the system s overall objective or of This definition encapsulates the notion of practical reasoning analysed in [3] and [24] general strategies for communication and coordination. In other approaches, the main focus is on coordination strategies between multiple decision makers [15, 32, 34, 78, 79]. Consequently, the mental apparatus and inferential mechanisms of agents are obscured under the mere assumption that agents have their own decision making expertise which frequently has to be coordinated when the goals undertaken by individual agents are related. However, in the majority of ....

S. Cammarata, D. McArthur and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of the International Joint Conference On Artificial Intelligence, pages 767-770, Karlsruhe, Germany, 1983.

....protocols specified in advance by the system designer. Therefore each agent has little knowledge of the system s overall objective or of general strategies for communication and coordination. In other approaches, the main focus is on coordination strategies between multiple decision makers [15, 32, 34, 37, 78, 79]. Consequently, the mental apparatus and inferential mechanisms of agents are obscured under the mere assumption that agents have their own decision making expertise which frequently has to be coordinated when the goals undertaken by individual agents are related. This definition encapsulates the ....

S. Cammarata, D. McArthur and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of the International Joint Conference On Artificial Intelligence, pp. 767--770, Karlsruhe, 1983.

....its structure and operation at run time is highly valuable for many application domains; see, e.g. 2, 11, 10] In this paper, we investigate the performance of a particular approach to dynamically reallocating tasks and resources in a multi agent system. This adaptive organizational policy ([1]) is called trace (Task and 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 ....

S. Cammarata, D. McArthur, and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of the Eighth International Joint Conference on Articial Intelligence (IJCAI-83), Karlsruhe, Federal Republic of Germany, 1983.

....tend to have homogeneous and rather small grained agents. Multi agent Planning. In multi agent planning, the agents of a society locally plan their future actions and try to coordinate their behavior by combining the local plans to a consistent global plan. In centralized multi agent planning [CMS83] the agents rst compute local plans and send them to a central coordinating agent. On receipt of all (partial) local plans, the coordinating agent analyzes them in order to identify potential inconsistencies and con icting interactions. The coordinating agent then tries to modify the partial ....

Stephanie Cammarata, David McArthur, and Randall Steeb. Strategies of cooperation in distributed problem solving. In IJCAI-83, pages 767-770, 1983.

....game. This naturally impacts on the robots cooperation coordination. In the multiagent system community communication and coordination issues are typically addressed by means of interaction protocols that give more or less exible guidelines to the agents in their communication with each other [3]. Given its knowledge bases, what it perceives from its outside world and the possible messages it gets from teammates, an agent communicates with others both through message passing (direct communication) and modi cation of the world (indirect communication) More precisely, interaction protocols ....

S. Cammarata, D. Mac Arthur, and R. Steeb. Strategies of cooperation in distributed problem solving. In A.H. Bond and L. Gasser, editors, Readings in Distributed Articial Intelligence, pages 102105. Morgan Kaufmann Publishers, Inc., San Mateo, CA, 1988.

....that respond and awards the task to the winning agent, who then goes on to perform that task, recruiting yet other agents to help if required. However, although DAI work has demonstrated success in a number of domains (e.g. distributed vehicle monitoring [21] and distributed air trac control [7]) the proposed solutions have rarely been demonstrated as directly applicable to situated agent (i.e. robotic) teams, which have to live in, and react to, a dynamic and uncertain environment using noisy sensors and e ectors, and a limited bandwidth, noisy communication mechanism. They typically ....

Stephanie Cammarata, David McArthur, and Randall Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of 8th International Joint Conference on Articial Intelligence, pages 767-770, 1983.

.... plan creation distributed NOAH, 1979, 4] DP NOAH like AI planner individual plan MA plan parent child relationships extending SAP to DP Konolige Nilsson 1980, 26] CP STRIPS like AI planner individual plan MA plan interacting (sub ) goals modeling MA plans Cammarata et al. 1983, [3] CP air traffic control DAI planner, simple body individual plan MA plan interactions between activity sequences detect resolve resource conflicts Georgeff, 1983, 15] CP DAI planner, simple body individual plan MA plan harmful (resource access) interactions plan synchronization partial ....

Cammarata, D., McArthur, R., Steeb, R., Strategies of Cooperation in Distributed Problem Solving, IJCAI-83, pp. 767-770.

.... problem in the area of Distributed Problem Solving systems includes, for example, Davis and Smith s work on the Contract Net [54] Cammarata et al. s work on strategies of cooperation that are needed for groups to solve shared tasks effectively in the context of collision avoidance in air traffic [2], Lesser and Erman s model of a distributed interpretation system that is able to function effectively even though processing nodes have inconsistent and incomplete information [31] and Carver et al. s work on agents with sophisticated models that support complex and dynamic interactions between ....

S. Cammarata, D. McArthur, and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of IJCAI-83, 1983.

....entities, even though each sensor agent saw only a part of the environment. They reported results using both an hierarchical organization, as well as an anarchic committee organization, and found that the latter was as good as, and sometimes better than the former. Cammarata and coauthors[1] espouse strategies for cooperation. They analyze the problems faced by the groups of agents involved in distributed problem solving, and infer a set of requirements on information distribution and organizational policies. They point out that in a DPS scenario, different agents may have different ....

S. Cammarata et al., Strategies of Cooperation in Distributed Problem Solving, Readings in Distributed Artificial Intelligence (Bond and Gasser, eds.), Morgan Kaufmann, 1988, pp. 102--105.

....entities, even though each sensor agent saw only a part of the environment. They reported results using both an hierarchical organization, as well as an anarchic committee organisation, and found that the latter was as good as, and sometimes better than the former. Cammarata and coauthors[1] espouse strategies for cooperation. They analyze the problems faced by the groups of agents involved in distributed problem solving, and infer a set of requirements on information distribution and organizational policies. They point out that in a DPS scenario, different agents may have different ....

S. Cammarata et al., Strategies of Cooperation in Distributed Problem Solving, Readings in Distributed Artificial Intelligence (Bond and Gasser, eds.), Morgan Kaufmann, 1988, pp. 102-- 105.

....moving entities, even though each sensor agent saw only a part of the environment. They reported results using both a hierarchical organization, as well as an anarchic committee organization, and found that the latter was as good as, and sometimes better than the former. Cammarata et al. Cet al...88] espouse strategies for cooperation. They analyze the problems faced by the groups of agents involved in distributed problem solving, and infer a set of requirements on information distribution and organizational policies. They point out that in a distributed problem solving scenario, different ....

S. Cammarata et al. Strategies of Cooperation in Distributed Problem Solving. In Bond and Gasser, editors, Readings in Distributed Artificial Intelligence, pages 102--105. Morgan Kaufmann, 1988.

....for articial agents, e.g. mobile robots. Taken as a whole, the AI literature is consistent with this choice, since each one of the individual 10 motivations in Table 1 is the object of theory and experimentation: physiological and safety (e.g. 10] icyberneticsj of the 50s) aOEliation (e.g. [2]) achievement (e.g. 5] self actualization (e.g. 9] Physiological Preserve battery level Safety Avoid stairways hostile agents AOEliation Achieve other agents goals Achievement Achieve its own goals Self Actualization Cover unknown areas Table 1: Human motivations, adapted from ....

S. Cammarata, D. McArthur, and R. Steeb. Strategies of Cooperation in Distributed Problem Solving. In Proceedings of the International Joint Conference on Articial Intelligence, pages 767770, Karlsruhe, West Germany, 1983.

....but also carries out a great deal of mental processing. Such a conservative approach is due to the high level of safety demanded of the system. Completely computerised controlled system have yet to show themselves capable of providing such integrity, which has led to many researchers in DAI [1, 2, 13, 14, 9] and CKBS [3] to investigate the feasibility of fully automating the current air traffic control system. Computers in current ATC system simply manipulate data for presentation to air traffic controllers. We visualize, in a fully automanted ATC system, that a computer will be characterised by its ....

Stephanie Cammarata, David McArthur, and Randall Steeb. Strategies of Cooperation in Distributed Problem Solving. In A.H. Bond and L. Gasser, editors, Readings in Distributed Artificial Intelligence, pages 102--105. Morgan Kaufmann, California, 1988.

No context found.

S. Cammarata, D. MacArthur, and R. Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of The International Joint Conference on Artificial Intelligence, pages 767--770, Karlsruhe, Germany, August 1983.

No context found.

S. Cammarata, D. McArthur, and R. Steeb. Strategies of Cooperation in Distributed Problem Solving. In In Proceedings of the International Joint Conference On Artificial Intelligence, Karlsruhe, pages 767--770, 1983.

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Stephanie Cammarata, David McArthur, Randall Steeb (1983). Strategies of cooperation in distributed problem solving, application on ATC. N-2031-ARPA prepared for the Defense Advanced Research Project Agency.

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Stephanie Cammarata, David McArthur, and Randall Steeb. Strategies of cooperation in distributed problem solving. In Proceedings of the Eighth International Joint Conference on Artificial Intelligence, pages 767--770, Karlsruhe, West Germany, August 1983.

No context found.

Cammarata, Stephanie, McArthur, David and Steeb, Randall, "Strategies of Cooperation in Distributed Problem Solving", Readings in Distributed Artificial Intelligence, Alan H. Bond and Les Gasser (editor), Morgan Kauffman Pub. Inc., San Mateo, California, 1988.

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