Open-ended Development Research Articles

Math Learning With Realistic Mathematics Education Approach Based On Open-ended Problems

This study aims to determine the feasibility and effectiveness of learning mathematics using teaching materials in the form of LKPD with a Realistic Mathematics Education (RME) approach based on open-ended problems. The design used in this research is Research and Development with a development model developed by Dick and Carry. Subjects in this study were students of class X IPA at Al-bairuny Islamic Senior High School in the academic year 2020/2021. Design implementation is using One Group Pretest Posttest Design with instruments in the form of questionnaires and tests. Data on student's understanding of mathematical concepts were collected using instrument tests as many as 5 essay questions. The analysis technique used is descriptive quantitative and qualitative. The results showed that (1) the validation of teaching materials is categorized as valid with an average score of 84,89% based on the expert judgment as well as the percentage of student’s responses to learning media of 80,29% categorized as feasible. (2) the effectiveness of teaching materials to reach the achievement of student’s competence gets an average score of 80,88 of the student learning outcomes and percentage of classical completeness of 89,47% categorized as very good. Based on the results of research findings and discussion, obtained the conclusion that the mathematics LKPD with the Realistic Mathematics Education (RME) approach based on open-ended development is feasible and effective to be used in the teaching and learning process.

Human Forms: The Novel in the Age of Evolution. Ian Duncan. Princeton, NJ: Princeton University Press, 2019. Pp. xiii+290.

<i>Human Forms: The Novel in the Age of Evolution</i>. Ian Duncan. Princeton, NJ: Princeton University Press, 2019. Pp. xiii+290.

A hierarchical representation of behaviour supporting open ended development and progressive learning for artificial agents

One of the challenging aspects of open ended or lifelong agent development is that the final behaviour for which an agent is trained at a given moment can be an element for the future creation of one, or even several, behaviours of greater complexity, whose purpose cannot be anticipated. In this paper, we present modular influence network design (MIND), an artificial agent control architecture suited to open ended and cumulative learning. The MIND architecture encapsulates sub behaviours into modules and combines them into a hierarchy reflecting the modular and hierarchical nature of complex tasks. Compared to similar research, the main original aspect of MIND is the multi layered hierarchy using a generic control signal, the influence, to obtain an efficient global behaviour. This article shows the ability of MIND to learn a curriculum of independent didactic tasks of increasing complexity covering different aspects of a desired behaviour. In so doing we demonstrate the contributions of MIND to open-ended development: encapsulation into modules allows for the preservation and re-usability of all the skills acquired during the curriculum and their focused retraining, the modular structure serves the evolving topology by easing the coordination of new sensors, actuators and heterogeneous learning structures.

CHANGES IN RELIGIOUSNESS AMONG OLDER ADULTS FOLLOWING CANCER DIAGNOSIS

This study aims to identify the changes in individuals’ religious beliefs after receiving a cancer diagnosis. Open-ended religious development interviews were completed with 278 older adults (aged 55 to 102) in the northeast United States. Of these 278, 16 of the interviewees had received a cancer diagnosis within the previous two years. These older adults who report a cancer diagnosis describe few changes in their overall religiousness. On the contrary, these individuals describe longstanding, generally consistent patterns of religiousness that began early in life, most often related to their family upbringing. While most of these cancer-diagnosed individuals have sustained their religious involvement over time, a few have rejected or substantially modified their religious involvement for reasons unrelated to their recent diagnosis (e.g., most often due to marrying someone of a different faith tradition). In addition, those who received a cancer diagnosis describe their religious involvement primarily in terms of its emotional and social reward. These individuals report little complexity of religious belief - little questioning, little doubt in religious doctrine. Instead they report a straightforward, deep, comforting religious belief. This is in contrast to frequent critical comments on religious belief and behavior reported by healthy older adults in our sample. Such findings are in keeping with previous research that describes a more extrinsically oriented religious involvement among older adults who are ill or vulnerable. We discuss these findings in light of both social selectivity theory (E.g., Carstensen, 1992) and stress and coping theory (Lazarus & lazarus, 2006).

Toward Computational Motivation for Multi-Agent Systems and Swarms.

Motivation is a crucial part of animal and human mental development, fostering competence, autonomy, and open-ended development. Motivational constructs have proved to be an integral part of explaining human and animal behavior. Computer scientists have proposed various computational models of motivation for artificial agents, with the aim of building artificial agents capable of autonomous goal generation. Multi-agent systems and swarm intelligence are natural extensions to the individual agent setting. However, there are only a few works that focus on motivation theories in multi-agent or swarm settings. In this study, we review current computational models of motivation settings, mechanisms, functions and evaluation methods and discuss how we can produce systems with new kinds of functions not possible using individual agents. We describe in detail this open area of research and the major research challenges it holds.

An Open-Ended Approach to Piagetian Development of Adaptive Behavior

In this paper, we are interested in the open-ended development of adaptive behavior by infant humans in the context of embodied, enactive cognitive science. We focus on the sensorimotor development of an infant child from gestation to toddler and discuss what aspects of the body, brain, and environment could allow for the sort of leaps of complexity observed in the developing infant that has heretofore not been replicable by artificial means. We use the backdrops of Piagetian developmental principles and Sensorimotor Contingency Theory to discuss this process in terms of skill proficiency, and discuss biologically plausible means for achieving it by referring to predictive processing and the free energy principle. We also refer to the theory of affordances to examine the selection of appropriate behaviors in a complex environment, and investigate phenomenological accounts to discuss the intentionality inherent in the purposeful behaviors that develop. Throughout this paper we develop a functional account of infant development which is based on the aforementioned theories and which leads to a biologically realistic explanation for the theory laid out by Piaget consistent with the embodied and enactive views.

Time, History, and Tradition in the Fundamentalist Imagination

Fundamentalists—those ministers, theologians, and laymen who joined forces against theological liberalism in the late-nineteenth and early-twentieth centuries—cared deeply about history. In this sense they were no different from other protestants of their age, confronted with a historicized Bible and a world falling into the strict sequential order required by modernity. But fundamentalists were different. They viewed time in categories inherited from American protestant thought, as a logical unfolding of a single beginning rather than as open-ended development. This principle of “first things” lay behind their objections to evolution and biblical criticism, but also their stand on social issues, their insistence that the role of women could and should not progress and change over time. Among evangelicals today, the fundamentalist sense of time as the extension of full and complete beginnings still resonates, in opposition to abortion and homosexuality and in their continuing reverence for the American founding fathers. History can be powerfully immediate. For evangelicals, the Bible is not an ancient text about long-dead people but fully contemporary, and thus read not “literally,” as if every word were true, but as if time did not exist. Ultimately, however, history has no depth or traction, or any theological meaning, a parenthesis between the God-ordained beginning and end of time.

Social Skill Acquisition Model through Face-to-Face Interaction: Local Contingency for Open-Ended Development

Behavior associated with joint attention is among the most important human functionalities for communicating with others. Previous studies indicate that even a robot can learn these behavioral patterns as social skills through interaction with a modeled/real caregiver by contingency evaluation. However, existing mechanisms are too time-consuming, especially for implementation on a real-world interactive robot. Also, they are poor in the acquisition of complex skills. In this paper, we propose a fast mechanism that enables the acquisition of many complex social skills within a short interaction time. The mechanism is realized by the utilization of two significant ideas: evaluating contingency locally, and acquiring social skills by finding synergistic contributions of values in contingencies. A comparison of our proposed mechanism in a simple environment of computer simulation with other mechanisms in terms of speed, accuracy, complexity, and noise resistance confirms the superior performance of our mechanism. Further, experimental results obtained with the proposed mechanism in a more complex computer simulation environment, which more closely resembles a real-world environment, indicate that the mechanism can be applied in real-world interaction between a robot and a human.

Intrinsic motivations and open-ended development in animals, humans, and robots: an overview.

Intrinsic motivations and open-ended development in animals, humans, and robots: an overview.

Learning autonomy in two or three steps: linking open-ended development, authority, and agency to motivation

In this paper we connect open-ended development, authority, agency, and motivation through (1) an analysis of the demands of existing in a complex world and (2) environmental appraisal in terms of affordance content and the complexity to select appropriate behavior. We do this by identifying a coherent core from a wide range of contributing fields. Open-ended development is a structured three-step process in which the agent first learns to master the body and then aims to make the mind into a reliable tool. Preconditioned on success in step two, step three aims to effectively co-create an optimal living environment. We argue that these steps correspond to right-left-right hemispheric dominance, where the left hemisphere specializes in control and the right hemisphere in exploration. Control (e.g., problem solving) requires a closed and stable world that must be maintained by external authorities or, in step three, by the right hemisphere acting as internal authority. The three-step progression therefore corresponds to increasing autonomy and agency. Depending on how we appraise the environment, we formulate four qualitatively different motivational states: submission, control, exploration, and consolidation. Each of these four motivational states has associated reward signals of which the last three—successful control, discovery of novelty, and establishing new relations—form an open-ended development loop that, the more it is executed, helps the agent to become progressively more agentic and more able to co-create a pleasant-to-live-in world. We conclude that for autonomy to arise, the agent must exist in a (broad) transition region between order and disorder in which both danger and opportunity (and with that open-ended development and motivation) are defined. We conclude that a research agenda for artificial cognitive system research should include open-ended development through intrinsic motivations and ascribing more prominence to right hemispheric strengths.

A game theoretic framework for incentive-based models of intrinsic motivation in artificial systems

An emerging body of research is focusing on understanding and building artificial systems that can achieve open-ended development influenced by intrinsic motivations. In particular, research in robotics and machine learning is yielding systems and algorithms with increasing capacity for self-directed learning and autonomy. Traditional software architectures and algorithms are being augmented with intrinsic motivations to drive cumulative acquisition of knowledge and skills. Intrinsic motivations have recently been considered in reinforcement learning, active learning and supervised learning settings among others. This paper considers game theory as a novel setting for intrinsic motivation. A game theoretic framework for intrinsic motivation is formulated by introducing the concept of optimally motivating incentive as a lens through which players perceive a game. Transformations of four well-known mixed-motive games are presented to demonstrate the perceived games when players' optimally motivating incentive falls in three cases corresponding to strong power, affiliation and achievement motivation. We use agent-based simulations to demonstrate that players with different optimally motivating incentive act differently as a result of their altered perception of the game. We discuss the implications of these results both for modeling human behavior and for designing artificial agents or robots.

One Trigger – Two Outcomes: The Role of EU Integration in Boosting and Eroding the Balkan Ethno-National Identities; The Case of Bulgaria and of (F.Y.R. of) Macedonia

This research focuses on mutations in national identities in contemporary Balkan context. It takes nations as dynamic communities, sharing some basic cultural codes of understanding. Having a common language is certainly a facilitating factor in such interpretative social activity. On the Balkans, despite the widespread national myths, nations are fairly recent phenomena.Multiple causal mechanisms, socially based or state-based, material or ideal, have helped painting the current picture of national communities. Unlike some authors within the literature, I do not see this process as irrevocably settled. The volcanoes may look extinguished, but new processes take place under the surface. Each new fundamental shift in the continental plate creates opportunities for renegotiating national contracts and galvanizing hidden social forces. European integration represents such a fundamental shift. It erodes from both above and below the principle that, according to Weber, state is a human community that successfully claims the monopoly of the legitimate use of physical force within a given territory. Within the process of European integration member states give up their sovereignty within particular domains; their citizens find new channels for expressing grievances and influencing domestic political actors. People start questioning whether it is worth taking part in national political process instead of switching allegiance to supranational political bodies. And this process of integration is still an open-ended development that will hardly settle in a near future. This research, based on an interpretative and constructivist paradigm, provides findings as to what are the effects of this integration on state-owning national communities in the Balkans. It takes two cases, Bulgaria and Macedonia, as examples of states already within the Union and still waiting to become members. It uses qualitative methodology, mainly semi-directive biographical interviews and non-participant ethnographic observations from three field trips to these countries between 2009 and 2011 as part of my doctoral research question on the effects of European integration on political culture in post-communist countries. The findings confirm that these two national communities, far from being static objects, are in a state of perpetual motion. Informants report more attachment to or detachment from their respective national communities as a direct result of European integration as an interpretative process. People may become more or less Bulgarian, or Macedonian, or European; or they may become simultaneously more present within their respective national communities and the new supranational identity. There are many, instead of a single cultural trajectory.

Developmental modelling with SDS

This paper describes modelling methods based on biological development for use in computer graphics applications, specifically the automated growth and development of complex organic shapes that are difficult to model directly. We examine previous approaches, including grammar-based methods, embedded systems and cellular models. Each system can be classified as endogenous (internally determined) or exogenous (externally determined), with some models exhibiting features of both. We then introduce a new model, the Simplicial Developmental System (SDS), which simulates individual cells embedded in a physical environment, with cell division, movement and growth controlled by morphogenetic chemical simulation. SDS uses a tetrahedral mesh as its base representation for geometric modelling and physical simulation. Cell growth, movement and division are determined by simulating chemical morphogens that are diffused between cells according to a set of user defined rules. We discuss the advantages and disadvantages of this model in terms of the competing goals of user control, developmental complexity and open-ended development (the ability to generate new component structures without explicit specification). Examples highlighting the strengths of the model are illustrated.

Reproducing Interaction Contingency Toward Open-Ended Development of Social Actions: Case Study on Joint Attention

How can human infants gradually socialize through interaction with their caregivers? This paper presents a learning mechanism that incrementally acquires social actions by finding and reproducing the contingency in interaction with a caregiver. A contingency measure based on transfer entropy is used to select the appropriate pairs of variables to be associated to acquire social actions from the set of all possible pairs. Joint attention behavior is tested to examine the development of social actions caused by responding to changes in caregiver behavior due to reproducing the found contingency. The results of computer simulations of human-robot interaction indicate that a robot acquires a series of actions related to joint attention such as gaze following and alternation in an order that almost matches the infant development of joint attention found in developmental psychology. The difference in the order between them is discussed based on the analysis of robot behavior, and then future issues are given.

CREATING NOVEL GOAL-DIRECTED ACTIONS AT CRITICALITY: A NEURO-ROBOTIC EXPERIMENT

The present study examines the possible roles of cortical chaos in generating novel actions for achieving specified goals. The proposed neural network model consists of a sensory-forward model responsible for parietal lobe functions, a chaotic network model for premotor functions and prefrontal cortex model responsible for manipulating the initial state of the chaotic network. Experiments using humanoid robot were performed with the model and showed that the action plans for satisfying specific novel goals can be generated by diversely modulating and combining prior-learned behavioral patterns at critical dynamical states. Although this criticality resulted in fragile goal achievements in the physical environment of the robot, the reinforcement of the successful trials was able to provide a substantial gain with respect to the robustness. The discussion leads to the hypothesis that the consolidation of numerous sensory-motor experiences into the memory, meditating diverse imagery in the memory by cortical chaos, and repeated enaction and reinforcement of newly generated effective trials are indispensable for realizing an open-ended development of cognitive behaviors.

Multilayer in-place learning networks for modeling functional layers in the laminar cortex

Currently, there is a lack of general-purpose in-place learning networks that model feature layers in the cortex. By "general-purpose" we mean a general yet adaptive high-dimensional function approximator. In-place learning is a biological concept rooted in the genomic equivalence principle, meaning that each neuron is fully responsible for its own learning in its environment and there is no need for an external learner. Presented in this paper is the Multilayer In-place Learning Network (MILN) for this ambitious goal. Computationally, in-place learning provides unusually efficient learning algorithms whose simplicity, low computational complexity, and generality are set apart from typical conventional learning algorithms. Based on the neuroscience literature, we model the layer 4 and layer 2/3 as the feature layers in the 6-layer laminar cortex, with layer 4 using unsupervised learning and layer 2/3 using supervised learning. As a necessary requirement for autonomous mental development, MILN generates invariant neurons in different layers, with increasing invariance from earlier to later layers and the total invariance in the last motor layer. Such self-generated invariant representation is enabled mainly by descending (top-down) connections. The self-generated invariant representation is used as intermediate representations for learning later tasks in open-ended development.

A MULTILAYER IN-PLACE LEARNING NETWORK FOR DEVELOPMENT OF GENERAL INVARIANCES

Currently, there is a lack of general-purpose, in-place learning engines that incrementally learn multiple tasks, to develop "soft" multi-task-shared invariances in the intermediate internal representation while a developmental robot interacts with its environment. In-place learning is a biologically inspired concept, rooted in the genomic equivalence principle, meaning that each neuron is responsible for its own development while interacting with its environment. With in-place learning, there is no need for a separate learning network. Computationally, biologically inspired, in-place learning provides unusually efficient learning algorithms whose simplicity, low computational complexity, and generality are set apart from typical conventional learning algorithms. We present in this paper the multiple-layer in-place learning network (MILN) for this ambitious goal. As a key requirement for autonomous mental development, the network enables both unsupervised and supervised learning to occur concurrently, depending on whether motor supervision signals are available or not at the motor end (the last layer) during the agent's interactions with the environment. We present principles based on which MILN automatically develops invariant neurons in different layers and why such invariant neuronal clusters are important for learning later tasks in open-ended development. From sequentially sensed sensory streams, the proposed MILN incrementally develops a hierarchy of internal representations. The global invariance achieved through multi-layer invariances, with increasing invariance from early layers to the later layers. Experimental results with statistical performance measures are presented to show the effects of the principles.

Task Transfer by a Developmental Robot

Scaffolding is a process of transferring learned skills to new and more complex tasks through arranged experience in open-ended development. In this paper, we propose a developmental learning architecture that enables a robot to transfer skills acquired in early learning settings to later more complex task settings. We show that a basic mechanism that enables this transfer is sequential priming combined with attention, which is also the driving mechanism for classical conditioning, secondary conditioning, and instrumental conditioning in animal learning. A major challenge of this work is that training and testing must be conducted in the same program operational mode through online, real-time interactions between the agent and the trainers. In contrast with former modeling studies, the proposed architecture does not require the programmer to know the tasks to be learned and the environment is uncontrolled. All possible perceptions and actions, including the actual number of classes, are not available until the programming is finished and the robot starts to learn in the real world. Thus, a predesigned task-specific symbolic representation is not suited for such an open-ended developmental process. Experimental results on a robot are reported in which the trainer shaped the behaviors of the agent interactively, continuously, and incrementally through verbal commands and other sensory signals so that the robot learns new and more complex sensorimotor tasks by transferring sensorimotor skills learned in earlier periods of open-ended development

Sorai and xunzi on the construction of the way1

While Sorai's intellectual debt to Xunzi is often mentioned, the similarities between their views have not often been explored at length in English2.2 Further, while Maruyama Masao does compare the two thinkers in his influential monograph Studies in the Intellectual History of Tokugawa Japan, he stresses (apparent) differences between Xunzi and Sorai, in order to hail Sorai's uniqueness. Without meaning to take anything away from Sorai as an independent thinker, I maintain that with regard to precisely those views for which Sorai is lauded as unique—that dao is a product of real people that evolved over time and continues to evolve—his position was also held by Xunzi. In addition, there is a related yet rarely highlighted aspect of Xunzi's thought that is also acknowledged by Sorai. That is, virtues acquired by participating in the way in turn qualify one to contribute to its continuous open-ended development.

Are Multiple Measures Meaningful?: Lessons From a Statewide Performance Assessment

For practical, psychometric, and pedagogical reasons, strong interest exists in developing multiple-measure constructed-response items for use in large-scale performance assessments. Items that can be scored for evidence of proficiency in 2 or more content areas raise questions, however, about the "fit" between various content areas and the possibility of sending cross-messages or confounding different content demands. To determine the factors that contribute to or compromise the effectiveness of multiscored items, in this study we combine analysis of statewide score data from the 1996 Maryland School Performance Assessment Program tests, administered at Grades 3, 5, and 8, with systematic analysis of 60 activities providing measures of writing, language usage (LU), or both, as well as one or more content areas. Although test developers to date have had greater success in creating writing/LU items that can also be scored for reading and social studies than for mathematics and science, we argue for the validity of multiple-measure items across all content areas and suggest that, across content areas, successful multiple-measure items (a) make information sources explicit and allow students to draw on both text-based and personal knowledge; (b) identify the specific content area skills or concepts being assessed; (c) permit open-ended development; (d) maintain a good fit between content demands and the rhetorical situation, creating an authentic writer-audience relationship; and (e) are uncluttered, focused, and direct, with good recall capability. Thus, we suggest that test developers reorient their concerns from the difficulty of items to identifying elements of multiple measure activities that facilitate or impede students' ability to demonstrate what they know and can do in different content areas.