Learning with Delayed Synaptic Plasticity

The plasticity property of biological neural networks allows them to perform learning and optimize their behavior by changing their configuration. Inspired by biology, plasticity can be modeled in artificial neural networks by using Hebbian learning rules, i.e. rules that update synapses based on the neuron activations and reinforcement signals. However, the distal reward problem arises when the reinforcement signals are not available immediately after each network output to associate the neuron activations that contributed to receiving the reinforcement signal. In this work, we extend Hebbian plasticity rules to allow learning in distal reward cases. We propose the use of neuron activation traces (NATs) to provide additional data storage in each synapse to keep track of the activation of the neurons. Delayed reinforcement signals are provided after each episode relative to the networks' performance during the previous episode. We employ genetic algorithms to evolve delayed synaptic plasticity (DSP) rules and perform synaptic updates based on NATs and delayed reinforcement signals. We compare DSP with an analogous hill climbing algorithm that does not incorporate domain knowledge introduced with the NATs, and show that the synaptic updates performed by the DSP rules demonstrate more effective training performance relative to the HC algorithm.Comment: GECCO201

Limited Evaluation Cooperative Co-evolutionary Differential Evolution for Large-scale Neuroevolution

Many real-world control and classification tasks involve a large number of features. When artificial neural networks (ANNs) are used for modeling these tasks, the network architectures tend to be large. Neuroevolution is an effective approach for optimizing ANNs; however, there are two bottlenecks that make their application challenging in case of high-dimensional networks using direct encoding. First, classic evolutionary algorithms tend not to scale well for searching large parameter spaces; second, the network evaluation over a large number of training instances is in general time-consuming. In this work, we propose an approach called the Limited Evaluation Cooperative Co-evolutionary Differential Evolution algorithm (LECCDE) to optimize high-dimensional ANNs. The proposed method aims to optimize the pre-synaptic weights of each post-synaptic neuron in different subpopulations using a Cooperative Co-evolutionary Differential Evolution algorithm, and employs a limited evaluation scheme where fitness evaluation is performed on a relatively small number of training instances based on fitness inheritance. We test LECCDE on three datasets with various sizes, and our results show that cooperative co-evolution significantly improves the test error comparing to standard Differential Evolution, while the limited evaluation scheme facilitates a significant reduction in computing time

Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions

A fundamental aspect of learning in biological neural networks is the plasticity property which allows them to modify their configurations during their lifetime. Hebbian learning is a biologically plausible mechanism for modeling the plasticity property in artificial neural networks (ANNs), based on the local interactions of neurons. However, the emergence of a coherent global learning behavior from local Hebbian plasticity rules is not very well understood. The goal of this work is to discover interpretable local Hebbian learning rules that can provide autonomous global learning. To achieve this, we use a discrete representation to encode the learning rules in a finite search space. These rules are then used to perform synaptic changes, based on the local interactions of the neurons. We employ genetic algorithms to optimize these rules to allow learning on two separate tasks (a foraging and a prey-predator scenario) in online lifetime learning settings. The resulting evolved rules converged into a set of well-defined interpretable types, that are thoroughly discussed. Notably, the performance of these rules, while adapting the ANNs during the learning tasks, is comparable to that of offline learning methods such as hill climbing.Comment: Evolutionary Computation Journa

Analysis of differences in Muscle Power for female university students majoring in sports according to BMI levels

Muscle Power (often expressed in terms of explosive strength or explosive force) is required in most sports activities that involve intense and rapid contractions. Purpose: Identifying the dif-ferences and their significance, between the muscle strength values for the female students of the Faculty of Physical Education and Sports, according to their classification by BMI levels. Materi-al and method: 77 female students of the Faculty of Physical Education and Sport from Galati were evaluated through 6 upper body muscle power tests (30s Plyometric Push-Ups, Shot put, Medicine ball chest throw, Overhead Medicine Ball Throw-forward, Overhead, Medicine Ball Throw-backward, Overhand ball throw) and 7 lower body muscle power tests (Speed Test 10m, Standing Long Jump Test, Vertical Jump Test, 3-Hop Test, 30s Continuous vertical jumps, 30s Lateral double leg hop test, The multiple 5 bounds test). The groups were divided according to BMI levels (underweight 11 cases, normal weight 53 cases and overweight 13 cases). The non-parametric Kruskal–Wallis and Mann-Whitney U tests were used to assess the differences be-tween groups. Results: Arithmetic average values indicate the superiority of underweight and normal-weight women for lower-body strength and overweight and normal-weight women for upper-body strength, especially for heavy objects throw variants. However, performance differ-ences (assessed by ranks) are in most cases insignificant (Z values correspond to thresholds P>0.05). The only exceptions with significant differences (P<0.05) are for Overhead Medicine Ball Throw-forward (with the superiority of the overweight over the underweight) and Shot put - track and field (with the superiority of the overweight over the underweight). Conclusion: The constant involvement of female students in curricular and sports physical activities mitigates the differences between the muscle power of the 3 BMI categories. However, the small numerical composition - for the underweight and overweight groups - does not allow the generalization of the results, as studies on larger samples are needed and have common concerns related to the specifics of the sports practiced

The influence of the specificity of sports specializations on the values of muscle power for female university students

Background: Explosive strength or muscle power plays a decisive role in the motor performance of all athletes. Purpose: Analysis of muscle strength variations for female students of the Faculty of Physical Education and Sport/undergraduate level, according to sports specializations. Mate-rial and method: The study included 77 women (age = 20.48 ± 1.37 years, weight = 58.79 ± 8.92 kg, height = 166.24 ± 7.13 cm), divided into 3 evaluation subgroups (Non-athletes/NA = 40 cases, Team sports games/TSG = 17 cases and IS/Individual sports = 20 cases). Explosive strength rating was based on 7 lower body tests and 6 upper body tests. Manova parametric techniques were applied. Results: The analysis of variance indicates significant differences between the 3 defined groups, the F values correspond to thresholds p 0.05). Top performance values are dominated by sprinters and volleyball players for the low-er body, respectively by handball, volleyball and karate players for the upper body, as-pects confirmed by the studied sources. Conclusion: We did not identify significant differences be-tween the groups of athletes (TSG and IS), and the top values according to sports specialization reinforce the results of other similar studies, the specific effort obviously infusing the perfor-mance in the muscle strength tests

ASPECTS REGARDING THE VARIABILITY OF SOME PHYSICAL AND CHEMICAL PROPERTIES OF THE SOILS IN THE BĂNDOIU AREA, THE GREAT BRĂILA ISLAND

The current status of Great Brăila Island is the result of an extensive activity of damming/draining/land reclamation of the Brăila Swamp with the aim to be used in agriculture. The final areas obtained from this complex activity preserve the specific variability of the flood areas. In order to be used in agricultural purposes, they need crop technologies which capitalize the physical and chemical soil properties. In order to highlight this variability, physical and chemical analysis on soil samples have been done. The analyzes highlighted the following: the soil texture is uniform (clayey and clay-loamy); the indicators characterizing the structural soil state indicate a good structural aggregation; soil reaction is weakly alkaline on the profile for the entire area; humus content varies from low to medium; the total nitrogen content varies from low to high (the vast majority of samples having medium contents); available phosphorus content varies from high to very high; available potassium content ranges from medium to very high; the total content of soluble salts indicates non-saline soils, while the total cation exchange capacity has medium and high values. The statistical analysis of the studied indicators indicates a coefficient of variation with values between 1.99% for the soil reaction and 53.17% for the structural instability index. Detailed analysis of these coefficients indicate a higher variability for the easily exchangeable indicators (such as nutrient supply) and a lower variability for stable elements (total cation exchange capacity, soil texture and soil reaction, being dependent on parent material). The results of the study highlights a relative homogeneity of the area, the indicators varying inside the same class of values, allowing the application of homogenous agricultural technologies on the study area

A new approach to balance dental fear and anxiety by using BachTM Flower Therapy

Treatments in dentistry currently consist of an interdisciplinary approach, including (but not necessarily limited to) the holistic perspective. The different fields of allopathic and complementary medicine are used together to ensure not only a high-quality restorative treatment, but also to provide patients with psychological and emotional support. This perspective also applies to dental anxiety, which consists of complex (emotional, vegetative and psychomotor) manifestations. One of the most well-known complementary therapies for reducing dental fear and anxiety is BachTM Flower Therapy. Even if the mechanism of action of this therapy is not yet scientifically documented, notable results have been and continue to be reported in the literature in several clinical studies on patients with dental diseases. It is indicated for both adults and children, in the latter when they go through major biological changes, such as primary and permanent dentition. As a conclusion, BachTM flower therapy is effective and complementary to dental treatments applied to patients, by reducing stress, anxiety, as well as creating a climate of peace, trust and confidence, both for the patient and the doctor. In addition, it is a relatively accessible and cheap form of care, with no significant adverse effects noted so far