Imitation learning is a promising route to better collaboration between humans and artificial agents. It will be most effective if the agent has some cognitive-level “understanding” of a human demonstrator’s intentions. Inferring intent is an example of abductive reasoning, wherein an agent explains the available evidence based on causal knowledge. Good explanations should satisfy some notion o...

Motivation) Tree reconciliation is an approach that explains the discrepancies between two evolutionary trees by a number of events such as speciations, duplications, transfers and losses. It has important applications in ecology, biogeography and genomics, for instance to decipher relationships between homologous sequences. (Results) We provide a fast and exact reconciliation algorithm accordi...

The motivated distance perception theory (Balcetis, 2015) paradoxically is too parsimonious to account for a variety of findings, including those of the author. The theory poorly defines the features of eliciting situations, which fails to constrain the theory making it non-falsifiable and allows for post-hoc interpretation of the effects. Finally, the theory ignores the complexity of the motiv...

Methods Partial sequences (c. 1400 bp) from the mitochondrial cytochrome b, 16S rDNA and COI genes were obtained from representative samples of the five species. Phylogenetic inference was carried out with maximum parsimony and maximum likelihood analyses. Parsimony networks were constructed for the Bermudian species Typhlatya iliffei and one Yucatan species Typhlatya mitchelli, to determine th...

Finding the best phylogenetic tree under the maximum parsimony optimality criterion is computationally difficult. We quantify the occurrence of such optima for well-behaved sets of data. When nearest neighbor interchange operations are used, multiple local optima can occur even for "perfect" sequence data, which results in hill-climbing searches that never reach a global optimum. In contrast, w...

Haplotype inference by pure parsimony (HIPP) is a wellknown paradigm for haplotype inference. In order to assess the biological significance of this paradigm, we generalize the problem of HIPP to the problem of finding all optimal solutions, which we call complete HIPP. We study intrinsic haplotype features, such as backbone haplotypes and fat genotypes as well as equal columns and decomposabil...

Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited number of samples. This paper is an investigation on two methods to improve generalization in GP-based learning: 1) the selection of the best-of-run individuals using a three data sets methodology, and 2) the applicati...

In his recent book Error Theory: History, Critique, Defence, Jonas Olson attempts to revive the argument from queerness originally made famous by J.L. Mackie. In this paper, we do three things. First, we eliminate four untenable formulations of the argument. Second, we argue that the most plausible formulation is one that depends crucially upon considerations of parsimony. Finally, we evaluate ...

Some wavelet-based methods for signal estimation in the presence of noise are reviewed in the context of the parsimonious representation of the underlying signal. Three approaches are considered. The first is based on the application of the MDL principle. The robustness of this method is improved in the second approach, by relaxing the assumption of known noise distribution following Huber’s wo...

This paper describes experiments with a genetic algorithm that combines parsimony with a novel gene regulation mechanism to carry out model selection. In effect, the GA orchestrates a competition among a community of models. Parsimony is implemented via the Akaike Information Criterion, and gene regulation uses a modulo function to overload the gene values. The approach is shown to be successfu...