J.O. Kephart, T. Hogg, and B.A. Huberman. Dynamics of Computational Ecosystems: Implication for DAI. Distributed Artificial Intelligence, 2, 1989.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... agents interact include communication between heterogeneous agents [9] forms of cooperation and communication and how they are achieved; Conflict resolution e.g. by negotiation [10] planning for multiple agents [11] emergent social behaviour [12] and societies and organisations of agents [13] [14]. These issues are discussed further in the next section. 1.3 An Anatomy of DAI Systems In this section we attempt to suggest some dimensions along which DAI systems should be compared and mention some important characteristics of DAI systems. Distributed Problem Solving and Multi Agent Systems ....

J.O. Kephart, T. Hogg and B.A. Huberman, 1987. Dynamics of Computational Ecosystems: Implications for DAI, in Distributed Artificial Intelligence 2 (Eds L. Gasser and M. N. Huhns), Morgan Kaufmann, pp.79-96.

.... during this period include Katia Sycara s work on using case based reasoning to allow bargaining parties to arrive at a compromise deal [41] and Hubermann and colleagues work on analyzing the dynamics of interactions between a large number of interacting agents following simple behavioral rules [42, 43]. In addition, two DAI testbeds developed during this period gave researchers a common platform to evaluate new coordination schemes and was also used as pedagogical tools in courses on DAI offered around the world [44, 45] The research issues that came to the forefront over the last five years ....

J. O. Kephart, T. Hogg, and B. A. Huberman. Dynamics of computational ecosystems: Implications for DAI. In Michael N. Huhns and Les Gasser, editors, Distributed Artificial Intelligence, volume 2 of Research Notes in Artificial Intelligence. Pitman, 1989.

....information, they would be severely restricted in their ability to estimate the value of deliberated relaxations. 3 On the other hand, if smart agents possess too accurate knowledge of market scarcities, this may induce overcompensation, slowing down convergence towards market equilibrium (cf. [2]) To cope with this phenomenon, various methods are conceivable. One could introduce a manipulatory component in the manager, allowing it to send slightly different market profiles to different agents. Or, 3 Actually, for reliable estimation of the risk associated with a specific conditional ....

Kephart, J.O., Hogg, T., Huberman, B.A.: Dynamics of Computational Ecosystems: Implications for DAI. In: L. Gasser and M. Huhns (Eds.), Distributed Artificial Intelligence, Vol. 2, Morgan Kaufmann Publishers (1989)

....of the resource due to congestion. Hence, there is a justified need for agents to seek out and move to resources with lesser usage. Other researchers have shown that such systems can exhibit oscillatory or chaotic behavior where agents continually move between resources (Hogg and Huberman, 1991; Kephart et al. 1989) resulting in lack of system stability and ineffective utilization of system resources. The case has also been made that the introduction of asynchronous decision making or heterogeneous decision making schemes can improve system convergence. We see our current work as providing a natural, ....

....little work has been done to investigate the benefits of limiting information access by agents. Hogg and Huberman (Hogg and Huberman, 1991) have analyzed a resource utilization problem similar to the one used here to study the effects of local decisions on group behavior (Hogg and Huberman, 1991; Kephart et al. 1989). Kephart et al. Kephart et al. 1989) show how system parameters like decision rate can produce stable equilibria, damped oscillations, persistent oscillations, or can lead the system into a chaotic phase. They also provide an analysis of how agents that monitor system behavior and accordingly ....

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Kephart, J. O., Hogg, T., and Huberman, B. A. (1989). Dynamics of computational ecosystems: Implications for DAI. In Huhns, M. N. and Gasser, L., editors, Distributed Artificial Intelligence, volume 2 of Research Notes in Artificial Intelligence. Pitman.

....factors as independent variables jointly determining the organizational performance. More complex 31 models such as these can result in many possible classes of organization environment system behaviors as identified in theories of complex systems such as Chaos, Punctuated Equilibria, etc. (Kephart, Hogg, and Huberman, 1989). Despite limitations of this sort, our belief is that pushing our model along its various dimensions will illuminate in a more precise manner, as exemplified in this paper, the relationship between task environmental, organization, and performance characteristics. Our methodology emphasizes ....

Kephart, J. O., T. Hogg and B. A. Huberman (1989), "Dynamics of computational ecosystems: implications for DAI," in L. Gasser and M. Huhns (Eds.) Distributed Artificial Intelligence, Vol. 2, pp. 79-95, London: Pitman; San Mateo, California: Morgan and Kaufmann.

....Therein lies one of the great strengths and weaknesses of multi agent systems. The strength is that this emergent functionality can be exploited by the multi agent system builder, to provide simple, robust cooperative behaviour. The weakness is that emergent functionality is akin to chaos [16]. In short, the dynamics of multi agent systems are complex, and can be chaotic. It is often difficult to predict and explain the behaviour of even a small number of agents; with larger numbers of agents, attempting to predict and explain the behaviour of a system is futile. Often, the only way to ....

J. O. Kephart, T. Hogg, and B. A. Huberman. Dynamics of computational ecosystems: Implications for DAI. In L. Gasser and M. Huhns, editors, Distributed Artificial Intelligence Volume II, pages 79--96. Pitman Publishing: London and Morgan Kaufmann: San Mateo, CA, 1989.

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J.O. Kephart, T. Hogg, and B.A. Huberman. Dynamics of Computational Ecosystems: Implication for DAI. Distributed Artificial Intelligence, 2, 1989.

No context found.

J. O. Kephart, T. Hogg, and B. A. Huberman, "Dynamics of computational ecosystems: Implications for DAI," in Distributed Artificial Intelligence, (L. Gasser and M. N. Huhns, eds.), ch. 4, pp. 79--95, San Mateo, CA: Morgan Kaufmann Publishers, 1989.

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