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

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

Nurturing Business Ecosystems for Growth in a Foreign Market: Incubating, Identifying and Integrating Stakeholders

This paper explores the process of nurturing a business ecosystem to facilitate corporate growth in an unfamiliar foreign market with high product uncertainty and no network resources. The authors conducted a qualitative, longitudinal study by examining a successful business case — ARM (a leader in microprocessor intellectual property) — to demonstrate how firms nurture their business ecosystems to develop in the Chinese market and to stimulate demand even with- out the advantages of resources and stabilized products. Based on the road map method, this paper develops a framework of creating a business ecosystem in three sequential stages namely, incubating complementary partners, identifying leader partners, and integrating ecosystem part- ners. The findings enrich classic international business and demand chain theories by highlighting different roles stakeholders adopt to cope with uncertain products in a foreign market. In practical terms, these findings also provide Mode 2 knowledge with application context (Gibbons et al., 1997) on entering new markets by building up an ecosystem

NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS

An agent may interact with its environment and learn complex tasks based on evaluative feedback through a process known as reinforcement learning. Reinforcement learning requires exploration of unfamiliar situations, which necessarily involves unknown and potentially dangerous or costly outcomes. Supervising agents in these situations can be seen as a type of nurturing and requires an investment of time usually by humans. Nurturing, one individual investing in the development of another individual with which it has an ongoing relationship, is widely seen in the biological world, often with parents nurturing their o spring. There are many types of nurturing, including helping an individual to carry out a task by doing part of the task for it. In arti cial intelligence, nurturing can be seen as an opportunity to develop both better machine learning algorithms and robots that assist or supervise other robots. Although the area of nurturing robotics is at a very early stage, the hope is that this approach can result in more sophisticated learning systems. This dissertation demonstrates the e ectiveness of nurturing through experiments involving the evolution of the parameters of a reinforcement learning algorithm that is capable of nding good policies in a changing environment in which the agent must learn an episodic task in which there is discrete input with perceptual aliasing, continuous output, and delayed reward. The results show that nurturing is capable of promoting the evolution of learning in such environments

Human nature and institutional analysis

This essay reviews some findings in cognition sciences and examines their consequences for the analysis of institutions. It starts by exploring how humans’ specialization in producing knowledge ensures our success in dominating the environment but also changes fast our environment. So fast that it did not give time to natural selection to adapt our biology, causing it to be potentially maladapted in important dimensions. A main function of institutions is therefore to fill the gap between the demands of our relatively new environment and our biology, still adapted to our ancestral environment as hunter-gatherers. Moreover, institutions are built with the available elements, which include our instincts. A deeper understanding of both aspects, their adaptive function and this recruitment of ancestral instincts, will add greatly to our ability to manage institutions.Evolution, biology, behavior, institutions

A Pedagogy of Deep Listening in E-Learning

This paper examines deep listening as a pedagogy in 21st century online education. The topic is situated in the intersubjectivity of computer-mediated communication in learning environments that foster transformative experiences. The transdisciplinary orientation of the paper includes the complex and overlapping lenses through which multiple ways of teaching, learning, and knowing are viewed and experienced in the context of fostering transformation in online education in a time of rapid growth in technological innovation, globalization, and significant environmental change. It transcends an individual disciplinary research and focus, bridging epistemologies to consider the felt sense of deep listening in the educator’s role

The Undergraduate as an Engaged Explorer

This paper asserts that most undergraduates leave Irish universities short-changed, never having been exposed to the riches of research. A re-conceptualisation of the research university is proposed, one founded on a culture of inquiry, interdisciplinarity and innovation. Scholarship is expanded to include engagement with communities, utilising the academy's unique multidisciplinary environment. It is argued that creativity and exploration should be essential elements in every undergraduate experience. A specific programme is used to exemplify how a responsible, civic and sustainable innovation culture can guide research and self-discovery, helping students understand how developing their own ventures can create value in society

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

Entrepreneurial leadership: what is it and how should it be taught?

Main ArticleWe offer a comprehensive review of the literature relating to entrepreneurial leadership, noting that there are diverse understandings of the concept and little exploration of how best to teach it. We next present empirical data from a survey of teaching practices at 51 HEIs in the UK that indicate little explicit teaching of entrepreneurial leadership. Drawing on this literature and data, we make recommendations for the design of teaching materials that emphasise the relevance of leadership in entrepreneurship education and of entrepreneurship in leadership education

Metaphors and Sense of Teaching: How These Constructs Influence Novice Teachers

This is the authors' accepted manuscript, post peer-review. The publisher's official version can be found at: http://dx.doi.org/10.1080/10476210500204887.The purpose of this study was to identify the root metaphors of secondary classroom teachers and to observe ways in which these constructs influence teachers’ work with their students and their environments. Specifically, five case studies of novice teachers were presented. Results indicated that the metaphor of life as a tree was the most common view and that all five participants held a similar childhood metaphor in which they tended to idealize childhood. Overall, the data showed the persistence of ideas that beginning teachers bring to their university preparation and those beliefs extend into actual classroom practice. Teacher development seemed to be more influenced by the schooling environment rather than the preservice preparation the teachers received. Furthermore, these novice teachers felt conflict between their held-beliefs and the reality of teaching and schooling. Implications for teacher educators and future research are included