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Additional resources for Autonomy Oriented Computing
For instance, both have been treated as distributed problem solving). 7 The chapter illustrates a search (optimization based) strategy for image segmentation and feature detection. From a computer vision point of view, compare this strategy with some traditional search based segmentation algorithms, and evaluate their performances with other computer vision segmentation benchmarks. 1. Introduction In the preceding chapters, we have provided the basic concepts and illustrations of AOC in problem solving.
B) When the count reaches a certain value, it is said that a triggering condition has been satisfied. This is in fact the case in our illustrative example, as the location of the entity is right next to the border of a shaded region. Thus, the entity will asexually self-reproduce some offspring entities within its local region. (c) At the following steps, the offspring will diffuse to new locations. By doing so, some of them will encounter new border feature locations as well and thereafter self-reproduce more entities.
These agents are usually heterogeneous entities, and different groups have different roles. , 1998]. The behavior of an individual agent is preprogrammed and can sometimes be complex. Complicated issues, such as negotiation and coordination, are of paramount importance. All these are usually part of the systems design, and hence require human interventions. AUTONOMY ORIENTED COMPUTING 12 Another example of multi-entity computation is ecology of computation [Hogg and Huberman, 1993, Huberman, 1988], where a population of heterogeneous computational systems share partial solutions to a common problem at hand.