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Relationships between internal and external metrics in co-evolution

Relationships between internal and external metrics in co-evolution,10.1109/CEC.2005.1555046,Elena Popovici,Kenneth A. De Jong

Relationships between internal and external metrics in co-evolution   (Citations: 9)
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Co-evolutionary algorithms (CEAs) have been applied to optimization and machine learning problems with often mediocre results. One of the causes for the unfulfilled expectations is the discrepancy between the external problem solving goal and the internal mecha- nisms of the algorithm. In this paper, we investigate in a principled way the relationships between the internal subjective metric used as fitness by a co-evolutionary al- gorithm and the external objective metric measuring the algorithm's progress towards the envisioned goal. We point out the complexity of these relationships and ex- plain their causes.
Conference: IEEE Congress on Evolutionary Computation - CEC , pp. 2800-2807, 2005
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    • ...She looked at the dynamics of individuals using fitness landscapes, explained the problem of convergence to the Nash Equilibrium with best response curves [25], analysed sequential and parallel CCEAs [26], investigated relationships between internal and external metrics [27]...

    Maksud Ibrahimovet al. Comparison of cooperative and classical evolutionary algorithms for gl...

    • ...While the concept of evolving subcomponents of a problem independently and coadaptively sounds natural and attractive, the dynamics of CCEA is far more complex as compared to EA [3]...
    • ...In an attempt to better understand the underlying dynamics of CCEA, empirical studies have focused on various aspects ‐ choice of collaborators [5], [6], interaction frequency [7], sequential and parallel versions of information exchange referred as update timing [8], disconnection between the external goal and the internal behavior of CCEA [3], etc...

    Tapabrata Rayet al. A cooperative coevolutionary algorithm with Correlation based Adaptive...

    • ...Despite their similarity in framework, coevolutionary learning and EAs are fundamentally different in how the fitness of a solution is assigned, leading to significantly different outcomes when applied to similar problems (e.g., different search behaviors on the space of solutions [7], [8])...
    • ...Even if a fitness function can be formulated, it may not be able to evaluate and differentiate between individual solutions to provide some gradient to direct the search when using EAs [8], [13]...
    • ...Coevolutionary pathologies are usually attributed to the use of relative fitness in the selection process of a coevolutionary learning system [8], [24]...
    • ...However, for this particular investigation, previous studies are restricted to simple problems or problems where the global view is known in advance [8], [11]...

    Siang Yew Chonget al. Measuring Generalization Performance in Coevolutionary Learning

    • ...Significant work has been done in this field by several researchers [16,17,18,19,20]...

    Matt Parkeret al. The Core: Evolving Autonomous Agent Control

    • ...We give here a brief description of best-response curves; for more details see [9], [7] and [8] 3 .I ff : DX × DY → R is the function to maximize, we define bestResponseX : DY → DX, bestResponseX(y0 )= argmaxx∈DX f(x, y0)...
    • ...3 In [8] the effect of the best-response curves was studied in the context of competitive coevolution...

    Elena Popoviciet al. Sequential versus Parallel Cooperative Coevolutionary Algorithms for O...

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