all publications as Word document
... Soltoggio, A, Bullinaria, JA, Mattiussi, C, Dürr, P, Floreano, D (Accepted for publication) Evolutionary advantages of neuromodulated plasticity in dynamic, rewardbased scenarios. In Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Sy ...
... Soltoggio, A, Bullinaria, JA, Mattiussi, C, Dürr, P, Floreano, D (Accepted for publication) Evolutionary advantages of neuromodulated plasticity in dynamic, rewardbased scenarios. In Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Sy ...
Cell division and migration in a `genotype` for neural
... The consequences of adopting a recursive mapping like the one just illustrated are several. First of all, we should consider that a recursive mapping can cause the development of very complicated structures on the basis of very simple genetic instructions. (Cf. the simple simulation experiments by D ...
... The consequences of adopting a recursive mapping like the one just illustrated are several. First of all, we should consider that a recursive mapping can cause the development of very complicated structures on the basis of very simple genetic instructions. (Cf. the simple simulation experiments by D ...
Cell division and migration in a `genotype` for neural networks (Cell
... The consequences of adopting a recursive mapping like the one just illustrated are several. First of all, we should consider that a recursive mapping can cause the development of very complicated structures on the basis of very simple genetic instructions. (Cf. the simple simulation experiments by D ...
... The consequences of adopting a recursive mapping like the one just illustrated are several. First of all, we should consider that a recursive mapping can cause the development of very complicated structures on the basis of very simple genetic instructions. (Cf. the simple simulation experiments by D ...
pptx - Electrical and Computer Engineering
... contain more than one entry per state-letter pair – When more than one transition is possible, a non-deterministic Turing machine branches and creating a new sequence of computation for each possible transition ...
... contain more than one entry per state-letter pair – When more than one transition is possible, a non-deterministic Turing machine branches and creating a new sequence of computation for each possible transition ...
KClustering
... data set. Therefore, it is difficult to discuss a runtime for the algorithm. For this reason center-based clustering algorithms are usually compared by the runtime of a single iteration. 2.2.4 Correctness ...
... data set. Therefore, it is difficult to discuss a runtime for the algorithm. For this reason center-based clustering algorithms are usually compared by the runtime of a single iteration. 2.2.4 Correctness ...
Feature Subset Selection - Department of Computer Science
... Naive Bayes is unable to learn these concepts and similar accuracy can be achieved through simply predicting the most frequent class value. Because CFS is a filter algorithm, the feature subsets chosen for Naive Bayes are the same as those chosen for IB1. The results for C4.5 (not shown) are less s ...
... Naive Bayes is unable to learn these concepts and similar accuracy can be achieved through simply predicting the most frequent class value. Because CFS is a filter algorithm, the feature subsets chosen for Naive Bayes are the same as those chosen for IB1. The results for C4.5 (not shown) are less s ...
Hilbert`s problems and contemporary mathematical logic
... unsettled questions pass before our minds and look over the problems which the science of to-day sets and whose solution we expect from the future. To such a review of problems the present day, lying at the meeting of the centuries, seems to me well adapted. For the close of a great epoch not only i ...
... unsettled questions pass before our minds and look over the problems which the science of to-day sets and whose solution we expect from the future. To such a review of problems the present day, lying at the meeting of the centuries, seems to me well adapted. For the close of a great epoch not only i ...
Project Information - Donald Bren School of Information and
... reduce the variance of the Monte Carlo estimator of the gradient in blackbox variational inference. Instead of taking samples from the variational distribution, we use importance sampling to take samples from an overdispersed distribution in the same exponential family as the variational approximati ...
... reduce the variance of the Monte Carlo estimator of the gradient in blackbox variational inference. Instead of taking samples from the variational distribution, we use importance sampling to take samples from an overdispersed distribution in the same exponential family as the variational approximati ...
Approaches to Artificial Intelligence
... One's approach to research in AI seems to depend to a large extent on what propert.ies of int.elligent behaviour one is most. impressed by. For some, it might be the evolut.ionary ant.ecedents of this behaviour in other animals; for others, its biological underpinnings in the central nervous systemj ...
... One's approach to research in AI seems to depend to a large extent on what propert.ies of int.elligent behaviour one is most. impressed by. For some, it might be the evolut.ionary ant.ecedents of this behaviour in other animals; for others, its biological underpinnings in the central nervous systemj ...
implicant based solver for xor boolean linear systems
... B0 with a view to address following two objectives. This approach is based on implicant computation of Boolean formulas recently announced in (Sule 2016). In this paper we present the application of the ideas for the XOR linear case. 1. Finding all solutions of the system. This is not addressed by t ...
... B0 with a view to address following two objectives. This approach is based on implicant computation of Boolean formulas recently announced in (Sule 2016). In this paper we present the application of the ideas for the XOR linear case. 1. Finding all solutions of the system. This is not addressed by t ...
The Efficient Outcome Set of a Bi-criteria Linear Programming and
... † Faculty of Applied Mathematics and Informatics, HUT, Vietnam. ...
... † Faculty of Applied Mathematics and Informatics, HUT, Vietnam. ...
Genetic algorithm
In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.