Nurturing as Safe Exploration Promotes the Evolution of Generalized Supervised Learning

The ability to learn is often a desirable property of intelligent systems which can make them more adaptive. However, it is difficult to develop sophisticated learning algorithms that are effective. One approach to the development of learning algorithms is to evolve them using evolutionary algorithms. The evolution of learning is interesting as a practical matter because harnessing it may allow us to develop better artificial intelligence; it is interesting also from a more theoretical perspective of understanding how the sophisticated learning seen in nature---including that of humans---could have arisen. A potential obstacle to the evolution of learning when alternative behavioral strategies (e.g., instincts) can evolve is that learning individuals tend to exhibit ineffective behavior before effective behavior is learned. Nurturing, defined as one individual investing in the development of another individual with which it has an ongoing relationship, is often seen in nature in species that exhibit sophisticated learning behavior. It is hypothesized that nurturing may be able to increase the competitiveness of learning in an evolutionary environment by ameliorating the consequences of incorrect initial behavior. The approach taken is to expand upon a foundational work in the evolution of learning to enable also the evolution of instincts and then examining the strategies evolved with and without a nurturing condition in which individuals are not penalized for mistakes made during a learning period. It is found that nurturing promotes the evolution of learning in these environments

On Reinforcement Learning, Nurturing, and the Evolution of Risk Neutral

Reinforcement learning depends on agents being learning individuals, and when agents rely on their instincts rather than gathering data and acting accordingly, the population tends to be less successful than a true RL population. ÒRiskinessÓ is the elementary metric for determining how willing to rely on learning an individual or a population is. With a high learning parameter, as we denote riskiness in this paper, agents find the safest option and seldom deviate from it, essentially using learning to become a non-learning individual. With a low learning rate, agents ignore recency entirely and seek out the highest reward, regardless of the risk. We attempt in this paper to evolve this Òrisk neutralityÓ in a population by adding a safe exploration nurturing period during which agents are free to explore without consequence. We discovered the environmental conditions necessary for our hypotheses to be mostly satisfied and found that nurturing enables agents to distinguish between two different risky options to evolve risk neutrality. Too long of a nurturing period causes the evolution to waver before settling on a path with essentially random results, while a short nurturing period causes a successful evolution of risk neutrality. The non-nurturing case evolves risk aversion by default as we expected from a reinforcement learning system, because agents are unable to distinguish between the good risk and bad risk, so they decide to avoid risks altogether.Noundergraduat

Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks

Biological plastic neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifetime learning. The interplay of these elements leads to the emergence of adaptive behavior and intelligence. Inspired by such intricate natural phenomena, Evolved Plastic Artificial Neural Networks (EPANNs) use simulated evolution in-silico to breed plastic neural networks with a large variety of dynamics, architectures, and plasticity rules: these artificial systems are composed of inputs, outputs, and plastic components that change in response to experiences in an environment. These systems may autonomously discover novel adaptive algorithms, and lead to hypotheses on the emergence of biological adaptation. EPANNs have seen considerable progress over the last two decades. Current scientific and technological advances in artificial neural networks are now setting the conditions for radically new approaches and results. In particular, the limitations of hand-designed networks could be overcome by more flexible and innovative solutions. This paper brings together a variety of inspiring ideas that define the field of EPANNs. The main methods and results are reviewed. Finally, new opportunities and developments are presented

Decision support continuum paradigm for cardiovascular disease: Towards personalized predictive models

Clinical decision making is a ubiquitous and frequent task physicians make in their daily clinical practice. Conventionally, physicians adopt a cognitive predictive modelling process (i.e. knowledge and experience learnt from past lecture, research, literature, patients, etc.) for anticipating or ascertaining clinical problems based on clinical risk factors that they deemed to be most salient. However, with the inundation of health data and the confounding characteristics of diseases, more effective clinical prediction approaches are required to address these challenges. Approximately a few century ago, the first major transformation of medical practice took place as science-based approaches emerged with compelling results. Now, in the 21st century, new advances in science will once again transform healthcare. Data science has been postulated as an important component in this healthcare reform and has received escalating interests for its potential for ‘personalizing’ medicine. The key advantages of having personalized medicine include, but not limited to, (1) more effective methods for disease prevention, management and treatment, (2) improved accuracy for clinical diagnosis and prognosis, (3) provide patient-oriented personal health plan, and (4) cost containment. In view of the paramount importance of personalized predictive models, this thesis proposes 2 novel learning algorithms (i.e. an immune-inspired algorithm called the Evolutionary Data-Conscious Artificial Immune Recognition System, and a neural-inspired algorithm called the Artificial Neural Cell System for classification) and 3 continuum-based paradigms (i.e. biological, time and age continuum) for enhancing clinical prediction. Cardiovascular disease has been selected as the disease under investigation as it is an epidemic and major health concern in today’s world. We believe that our work has a meaningful and significant impact to the development of future healthcare system and we look forward to the wide adoption of advanced medical technologies by all care centres in the near future.Open Acces

Bias in Perceptions of Parenting Roles: Analysis of Gender and Socioeconomic Status

After industrialization in the United States, men primarily moved from the farm to the workplace, leaving women responsible for the children and maintaining the household alone. This arrangement contributed to the so called tender years doctrine, which suggested that mothers were better caretakers of the children and should therefore receive sole custody. The preference for mothers continued until the 1960\u27s, after the women\u27s liberation movement, when a large portion of women moved from the home into the workforce. State statutes were later changed to establish gender-neutrality for the purposes of determining custody decisions and suggested the custody of children should be in their best interests. However, the change of language in the statutes did not change the results of most custody decisions; custody continued to be granted to the mother in most cases. Research suggests there has been a small increase in sharing custody of children but no increase in the number of fathers being awarded sole custody. A prior notion of who should get custody and what defines a good parent is likely wrought with gender stereotypes and bias. This study examined gender stereotypes related to parenting by sampling three occupational groups: judges, psychologists and college students. The significant discrepancy in the ratings of mothers versus fathers varied based on which occupational group was rating the vignette parent and what aspects of parenting were being rated. All three groups rated the vignette mother higher on overall parenting skills and empathic parenting behaviors, as compared to the father in the vignette. Also, as the age of the respondent increased, overall parenting skills ratings declined, indicating a more critical evaluation of parents. Evaluating parenting skills appears complex, individualized and partially influenced by sex-role stereotyping. Gender differences that are likely due to vignette characteristics were found, suggesting bias exists in the evaluation of parenting. However, it may not be an intentional bias for or against one gender, instead it is more likely personal perceptions entering into the decision-making process

An exploratory descriptive study of foster care and non-foster care adolescents' perceptions on self-esteem, 2002

This study examines perceptions on self-esteem of adolescents in foster care and non-foster care adolescents. The study was based on the premise that there is a statistical significant relationship between the perceptions on self-esteem of adolescents in foster care and non-foster care adolescents. A case study analysis approach was used to analyze the data gathered using the SPSS program. Descriptive analysis and frequencies are presented as percentages, frequency distribution, the Mean, the Standard Deviation, Chi-square test, and the T-test was used with a p-value of .05 to determine significant relationships between variables. The researcher found that the hypothesis was accepted and that there is a statistical significant relationship between the perceptions on self-esteem of adolescents in foster care and non-foster care adolescents. The conclusions drawn from the findings suggest that there is a need for more research that will contribute to elevate the awareness for services needed among this population

Altruism in psychotherapy: altruistic acts as an adjunct to psychotherapy

This study will explore the impact of altruism on the mind, brain, and body in order to investigate the potential value of using guided altruistic behavior as an adjunct to attaining the goals of psychotherapy. there is considerable evidence from religious and social practices across cultures, groups like Alcoholics Anonymous, and epidemiological research that point to the positive physical and psychological effects of helping others. This idea was initially stimulated by findings that demonstrated that altruism stimulates brain regions also important to the processes and goals of successful psychotherapy. It is hypothesized that engaging in altruistic behaviors will stimulate emotions, thoughts, and neurobiological processes that will enhance the therapeutic process from a biopsychosocial model. The relevant literature suggests that there may be a correlation between altruism and achieving the goals of therapy

Inclusive Inquiry. 14th Annual Research Week: Event Proceedings

Presentations of completed and ongoing research activity conducted by graduate and undergraduate students and faculty at University of the Incarnate Word. Coordinated and presented by the Office of Research and Graduate Studies