By Luc Lamontagne, Enric Plaza
This publication constitutes the refereed complaints of the twenty first overseas convention on Case-Based Reasoning examine and improvement (ICCBR 2014) held in Cork, eire, in September 2014. The 35 revised complete papers provided have been conscientiously reviewed and chosen from forty nine submissions. The displays hide quite a lot of CBR subject matters of curiosity either to researchers and practitioners together with case retrieval and model, similarity evaluation, case base upkeep, wisdom administration, recommender structures, multiagent structures, textual CBR, and functions to healthcare and machine games.
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Additional info for Case-Based Reasoning Research and Development: 22nd International Conference, ICCBR 2014, Cork, Ireland, September 29, 2014 - October 1, 2014. Proceedings
The other extreme case, namely β = 0, models a completely unreliable source reporting preferences at random. The probabilistic model outlined above is speciﬁed by two parameters: the ideal solution y ∗ and the (true) precision parameter β ∗ ∈ R+ . , any element of Y is an eligible candidate), or it might be restricted to a certain subset Y0 ⊆ Y of candidates. As mentioned before, the parameter vector θ∗ = (y ∗ , β ∗ ) ∈ Y0 × R∗ can be estimated from a given set (2) of observed preferences using the maximum likelihood principle.
Each sensor updates an estimate of the percentage of coverage of a set of global grid cells using a one-dimensional Kalman ﬁlter, which fuses data from multiple platforms (whose sensor views overlap). A Kalman ﬁlter allows us to control the rate at which cell uncertainty can grow or be reduced with guaranteed and predictable rates of convergence of each cell to its mean value. 4 Area Coverage Search Algorithm We use three parameters that can aﬀect how the AUVs search a geographical area during HADR missions, where we assume they all begin a scenario near a single, randomly selected point and follow a grazing area coverage algorithm .
Iv) In each iteration, a new candidate y query is determined, again based on (6), and given as a query to an underlying oracle. The oracle is a (possibly imperfect) information source that compares y query with the current best solution y • . The preference reported by the oracle is memorized by adding it to the preference set P0 = P(x0 ) associated with x0 , as well as to the set P of preferences used for guiding the search process. Moreover, the better solution is retained as the current best candidate.
Case-Based Reasoning Research and Development: 22nd International Conference, ICCBR 2014, Cork, Ireland, September 29, 2014 - October 1, 2014. Proceedings by Luc Lamontagne, Enric Plaza