Autonomous Dynamic Reconfiguration in Multi-Agent Systems: by Markus Hannebauer

By Markus Hannebauer

High conversation efforts and negative challenge fixing effects because of limited assessment are principal matters in collaborative challenge fixing. This paintings addresses those concerns by way of introducing the procedures of agent melting and agent splitting that allow person challenge fixing brokers to repeatedly and autonomously reconfigure and adapt themselves to the actual challenge to be solved.

The writer offers a legitimate theoretical origin of collaborative challenge fixing itself and introduces numerous new layout options and methods to enhance its caliber and potency, corresponding to the multi-phase contract discovering protocol for exterior challenge fixing, the composable belief-desire-intention agent structure, and the distribution-aware constraint specification structure for inner challenge solving.

The functional relevance and applicability of the techniques and strategies supplied are established by utilizing clinical appointment scheduling as a case study.

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An extended GRATE* [151] architecture has been used in the AADCare project [139, 138] to manage medical processes. The system is implemented in PROLOG and facilitates a rule-based reasoning procedure on unreliable knowledge. In [83] Fox and others present a description language, called PROforma, that has been used in the PROMPT project for formal knowledge and process representation. Solotorevsky and Gudes have applied their constraint approach to time tabling in hospitals [240]. Decker and Li apply their generalized partial global planning approach to patient scheduling [60].

To overcome this weakness, we will use a much broader notion of DCSPs in this work. We will generalize the notion of configuration such that it can handle any assignment of problem model elements to agents and extend the DCSP model to distributed constraint optimization problems (DCOPs). 3 Constraint Problems In problem solving one can usually distinguish situations in which one is only interested in finding a single solution to a given problem, from situations in which one is interested in finding a good or even the best solution to a given problem provided an ordering criterion that defines the desirableness of a solution.

Therefore, solving the optimal value and optimal solution variants typically yields a considerable amount of extra effort. The branch-and-bound approach known from integer programming is an example for this kind of meta-approaches. Since one is often not interested in the complete solution space of a constraint optimization problem but only in optimal solutions, we can weaken the notion of τ -solution space equivalence to compare constraint optimization problems. This leads to the notion of τ -solution equivalence.

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