AIMC Topic: Computer Simulation

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Machine Learning Biogeographic Processes from Biotic Patterns: A New Trait-Dependent Dispersal and Diversification Model with Model Choice By Simulation-Trained Discriminant Analysis.

Systematic biology
Current statistical biogeographical analysis methods are limited in the ways ecology can be related to the processes of diversification and geographical range evolution, requiring conflation of geography and ecology, and/or assuming ecologies that ar...

A Multiobjective Approach to Homography Estimation.

Computational intelligence and neuroscience
In several machine vision problems, a relevant issue is the estimation of homographies between two different perspectives that hold an extensive set of abnormal data. A method to find such estimation is the random sampling consensus (RANSAC); in this...

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing.

PloS one
We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by inc...

Controlling Individuals Growth in Semantic Genetic Programming through Elitist Replacement.

Computational intelligence and neuroscience
In 2012, Moraglio and coauthors introduced new genetic operators for Genetic Programming, called geometric semantic genetic operators. They have the very interesting advantage of inducing a unimodal error surface for any supervised learning problem. ...

Particle Swarm Optimization with Double Learning Patterns.

Computational intelligence and neuroscience
Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior o...

A Neural Network Approach to Intention Modeling for User-Adapted Conversational Agents.

Computational intelligence and neuroscience
Spoken dialogue systems have been proposed to enable a more natural and intuitive interaction with the environment and human-computer interfaces. In this contribution, we present a framework based on neural networks that allows modeling of the user's...

Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network.

Computational intelligence and neuroscience
Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure. Such systems driven by hub motors (in wheel motors) encounter previously defined and undef...

A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem.

Computational intelligence and neuroscience
The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the id...

Optimal Modality Selection for Cooperative Human-Robot Task Completion.

IEEE transactions on cybernetics
Human-robot cooperation in complex environments must be fast, accurate, and resilient. This requires efficient communication channels where robots need to assimilate information using a plethora of verbal and nonverbal modalities such as hand gesture...

Why do some neurons in cortex respond to information in a selective manner? Insights from artificial neural networks.

Cognition
Why do some neurons in hippocampus and cortex respond to information in a highly selective manner? It has been hypothesized that neurons in hippocampus encode information in a highly selective manner in order to support fast learning without catastro...