Examples of how LTP and LTD can control adaptively-timed learning that modulates attention and motor control are given. It is also suggested that LTP/LTD can play a role in storing memories. The distinction between match-based and mismatch-based learning may help to clarify the difference.

An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, when the (...) states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness. (shrink)

This article presents the framework and explores the measurement, correlates, and outcomes of creative adaptability, proposed here as the cognitive–behavioral-emotional ability to respond creatively and adaptively to stressful situations. Data collection was in April 2020, during the peak of the outbreak of the Coronavirus pandemic in Israel. In Study 1, a sample of 310 adults completed the newly developed CA scale, as well as spontaneity, openness to experience, creative self-efficacy, and well-being measurements. The results of exploratory and confirmatory factor analyses (...) corroborated the 9-item CA scale’s theorized underlying construct. The scale’s validity and reliability were also supported. Exploratory analyses suggested that the association between CA and well-being was mediated by creative self-efficacy and that CA may buffer the impact of individuals’ concern about Coronavirus on their well-being. In Study 2, short-term longitudinal data based on a sample of 71 students suggested that CA may predict lower psychological stress over time. Support for the CA scale’s internal consistency reliability was obtained and its test–retest reliability was established. Overall, the results shed light on this new construct as a potential protective factor. Implications for theory, research, and practice are discussed. (shrink)

The problem of adaptive finite-time fault-tolerant control and output constraints for a class of uncertain nonlinear half-vehicle active suspension systems are investigated in this work. Markovian variables are used to denote in terms of different random actuators failures. In adaptive backstepping design procedure, barrier Lyapunov functions are adopted to constrain vertical motion and pitch motion to suppress the vibrations. Unknown functions and coefficients are approximated by the neural network. Assisted by the stochastic practical finite-time theory and FTC theory, the proposed (...) controller can ensure systems achieve stability in a finite time. Meanwhile, displacement and pitch angle in systems would not violate their maximum values, which imply both ride comfort and safety have been enhanced. In addition, all the signals in the closed-loop systems can be guaranteed to be semiglobal finite-time stable in probability. The simulation results illustrate the validity of the established scheme. (shrink)

Adaptive Intelligence is a dramatic reappraisal and reframing of the concept of human intelligence. In a sweeping analysis, Robert J. Sternberg argues that we are using a fatally-flawed, outdated conception of intelligence; one which may promote technological advancement, but which has also accelerated climate change, pollution, the use of weaponry, and inequality. Instead of focusing on the narrow academic skills measured by standardized tests, societies should teach and assess adaptive intelligence, defined as the use of collective talent in service of (...) the common good. This book describes why the outdated notion of intelligence persists, what adaptive intelligence is, and how it could lead humankind on a more positive path. (shrink)

This paper proposes an adaptive neural network control approach for a direct-current system with full state constraints. To guarantee that state constraints always remain in the asymmetric time-varying constraint regions, the asymmetric time-varying Barrier Lyapunov Function is employed to structure an adaptive NN controller. As we all know that the constant constraint is only a special case of the time-varying constraint, hence, the proposed control method is more general for dealing with constraint problem as compared with the existing works on (...) DC systems. As far as we know, this system is the first studied situations with time-varying constraints. Using Lyapunov analysis, all signals in the closed-loop system are proved to be bounded and the constraints are not violated. In this paper, the effectiveness of the control method is demonstrated by simulation results. (shrink)

Using the methodology and findings of conversation analysis, we analyze changes in the talk of a man with aphasia (a language disorder acquired following brain damage) at two points in his spontaneous recovery period in the first months post-stroke. We note that in the earlier conversation (15 weeks post-stroke) two of the turn constructional methods he particularly makes use of are replacement (a form of repair) and extension. By the time of the latter conversation (30 weeks poststroke) these methods are (...) less prevalent, while another repair operation, insertion, is now used in a particular way not seen in the earlier conversation. We suggest that these methods are means by which the aphasic speaker adapts his limited linguistic resources to the demands of constructing a turn-at-talk in conversation in order to lessen the extent of repair and delay with the turn and thus lessen the exposure of his linguistic noncompetence and his identity as ‘different’, ‘disabled’, or ‘language impaired’. These turn constructional methods are dynamic and change as the speaker recovers. We suggest that communication disorders such as aphasia can be problematic not only because of difficulties they can cause in conveying information or producing other social actions, but also because they can create difficulties in the presentation of self in everyday life. (shrink)

The present research describes a novel adaptive anomaly detection method to optimize the performance of nonlinear and time-varying systems. The proposal integrates a centroid-based approach with the real-time identification technique Recursive Least Squares. In order to find anomalies, the approach compares the present system dynamics with the average (centroid) of the dynamics found in earlier states for a given setpoint. The system labels the dynamics difference as an anomaly if it rises over a determinate threshold. To validate the proposal, two (...) different datasets obtained from a level control plant operation have been used, to which anomalies have been artificially added. The results shown have determined a satisfactory performance of the method, especially in those processes with low noise. (shrink)

This paper presents an adaptive fuzzy sliding-mode controller for multiple Euler–Lagrange systems communicated with directed topology. Based on the graph theory and Lyapunov–Krasovskii functions, a delay-dependent sufficient condition for the existence of sliding surfaces is given in terms of linear matrix inequalities. The asymptotic stability is analyzed by using the Lyapunov method in the presence of unknown parametric dynamics, actuator faults, and time-varying delays. The usage of adaptive techniques is to adapt the unknown parameters so that the objective of globally (...) asymptotic stability is achieved. Finally, simulation results are provided to illustrate the effectiveness of the proposed control scheme. (shrink)

This paper develops an adaptive fixed-time trajectory tracking controller of an underactuated hovercraft with a prescribed performance in the presence of model uncertainties and unknown time-varying environment disturbances. It is the first time that the proposed method is applied to the motion control of the hovercraft. To begin with, based on the hovercraft's four degrees of freedom model, the virtual control laws are designed using an error transforming function and the fixed-time stability theory to guarantee that the position tracking errors (...) are constrained within the prescribed convergence rates and minimum overshoot. In addition, by combining the Lyapunov direct method and the adaptive radial basis function neural network, the actual control laws are designed to ensure that the velocity tracking errors converge to a small region containing zero while handling model uncertainties and external disturbances effectively. Finally, all tracking errors of the closed-loop system are uniformly ultimately bounded and fixed-time convergent. Results from a comparative simulation study verify the effectiveness and advantage of the proposed method. (shrink)

This paper presents an adaptive neural tracking control approach for a two-joint robotic manipulator with unknown time-varying delays. In order to work out the effect of unknown time-varying delays on the two-joint robotic manipulator, the appropriate Lyapunov–Krasovskii functionals and separation technology are chosen to settle this matter. The neural networks work as an approximator that has the advantage of estimating the unknown function in the system. In this paper, Lyapunov stability analysis can prove that all signals of the closed-loop system (...) are semiglobal uniformly ultimately bounded and the tracking error can converge to a compact neighborhood with respect to zero. The simulation consequences demonstrate the availability of the feedforward control approach. (shrink)

This paper studies the adaptive event-triggered finite-time tracking of output-constrained high-order nonlinear systems with time-varying powers. Due to the presence of multiple unknown powers and the consideration of event-triggered control, all the existing control methods of output-constrained nonlinear systems are inapplicable. By introducing nonlinear mappings, finite-time performance functions, and low-power and high-power terms into adding a power integrator technique and the relative threshold strategy, an adaptive state-feedback controller is designed to eliminate the effects caused by the output constraint and time-varying (...) powers. It is proved that all the closed-loop signals are bounded, the asymmetric time-varying output constraint is not violated, and the tracking error converges to a prescribed arbitrarily small region around zero in a preassigned finite time. Furthermore, the Zeno phenomenon can be avoided. Two simulation examples demonstrate the effectiveness of this control scheme. (shrink)

This paper studies the fixed-time trajectory tracking control problem of robot manipulators in the presence of uncertain dynamics and external disturbances. First, a novel nonsingular fixed-time sliding mode surface is presented, which can ensure that the convergence time of the suggested surface is bounded regardless of the initial states. Subsequently, a novel fast nonsingular fixed-time sliding mode control is developed so that the closed-loop system is fixed-time convergent to the equilibrium. By applying the proposed NFNFSMC method and the adaptive technique, (...) a novel adaptive nonsingular fixed-time control scheme is proposed, which can guarantee fast fixed-time convergence of the tracking errors to small regions around the origin. With the proposed control method, the lumped disturbance is compensated by the adaptive technique, whose prior information about the upper bound is not needed. The fixed-time stability of the trajectory tracking control under the proposed controller is proved by the Lyapunov stability theory. Finally, corresponding simulations are given to illustrate the validity and superiority of the proposed control approach. (shrink)

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping. Events in a time series can be experienced sequentially, or they can also be retrospectively viewed simultaneously, not experienced individually in real time. In one experiment, we studied the influence of presentation (...) mode on two sorts of judgment: predictions of the next event and estimation of the average value of all the events in the presented series. Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model—the adaptive anchoring model —to account for the difference between processing sequences of dynamically and statically presented stimuli. ADAM captures how variation in presentation mode produces variation in responses in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. (shrink)

In this paper, we mainly investigate the coordinated tracking control issues of multiple Euler–Lagrange systems considering constant communication delays and output constraints. Firstly, we devise a distributed observer to ensure that every agent can get the information of the virtual leader. In order to handle uncertain problems, the neural network technique is adopted to estimate the unknown dynamics. Then, we utilize an asymmetric barrier Lyapunov function in the control design to guarantee the output errors satisfy the time-varying output constraints. Two (...) distributed adaptive coordinated control schemes are proposed to guarantee that the followers can track the leader accurately. The first scheme makes the tracking errors between followers and leader be uniformly ultimately bounded, and the second scheme further improves the tracking accuracy. Finally, we utilize a group of manipulator networks simulation experiments to verify the validity of the proposed distributed control laws. (shrink)

This paper investigates the fixed-time coordinated control problem of six-degree-of-freedom dynamic model for multiple spacecraft formation flying with input quantization, where the communication topology is assumed directed. Firstly, a new multispacecraft nonsingular fixed-time terminal sliding mode vector is derived by using neighborhood state information. Secondly, a hysteretic quantizer is utilized to quantify control force and torque. Utilizing such a quantizer not only can reduce the required communication rate but also can eliminate the control chattering phenomenon induced by the logarithmic quantizer. (...) Thirdly, a 6-DOF fixed-time coordinated control strategy with adaptive tuning laws is proposed, such that the practical fixed-time stability of the controlled system is ensured in the presence of both upper bounds of unknown external disturbances. It theoretically proves that the relative tracking errors of attitude and position can converge into the regions in a fixed time. Finally, a numerical example is exploited to show the usefulness of the theoretical results. (shrink)

This article is related to the issue of fixed-time synchronization of different dimensional complex network systems with unknown parameters. Two suitable adaptive controllers and dynamic parameter estimations are proposed such that the complex network driving and response systems can be synchronized in the settling time. Based on fixed-time control theory and Lyapunov functional method, novel sufficient conditions are provided to guarantee the synchronization within the fixed times, and the settling times are explicitly evaluated, which are independent of the (...) initial synchronization errors. Finally, a numerical example is given to illustrate the effectiveness of the proposed control algorithms. (shrink)

Cet article présente les solutions utilisées pour le Corpus électronique des textes polonais des 17e et 18e siècles afin d’adapter son jeu de balises grammaticales à l’évolution du système morphologique qui a eu lieu au cours de la période. Les 17e et 18e siècles ont été marqués en effet par la formation d’une nouvelle catégorie grammaticale, appelée « masculine-personality » (Pl. *męskoosobowość*). Cette époque marque une transition de l’état ancien à l’état moderne et se caractérise par une variation significative des (...) terminaisons des formes plurielles N, A et V des noms masculins animés à cette époque. Par conséquent, le jeu de balises utilisé pour annoter le corpus, qui a été créé à l’origine pour le polonais moderne, a dû être légèrement modifié à cet égard. La deuxième partie de l’article décrit les recherches menées à l’aide de ce système d’annotation, qui ont montré que la différenciation des terminaisons flexionnelles des noms masculins personnels et impersonnels en polonais était déjà avancée au 17e siècle et presque achevée à la fin du 18e siècle. (shrink)

This article examines adaptive resource management as it has been applied to the US horseshoe crab fishery over the past decade. As a critical yet constructive exercise, I have three goals: to suggest how adaptive management, for all its promise, can still be improved; to add a nuanced case study to the literatures on the quantification of nature and environmental decision-making; and to use the example of ARM to make certain temporal aspects of contemporary natural resource management more salient to (...) science and technology studies scholars—that is, to show the ways in which time matters in environmental science, policy, and the analysis thereof. I draw attention to the time-related aspects of adaptive management by developing the notions of temporal orientation and chronological accountability. Temporal orientation refers to the time-based perspectives and epistemological commitments—that is, past-facing empiricism versus future-oriented modeling—that scientists of different types bring to bear on environmental problems. Chronological accountability refers to the missing link in adaptive forms of environmental governance: firm time lines and commitments to reflexively revisit management decisions. The time-related aspects of natural resource management deserve greater attention among both environmental managers and analysts of environmental policy. (shrink)

ABSTRACTNegative emotion influences cognitive control, and more specifically conflict adaptation. However, discrepant results have often been reported in the literature. In this study, we broke down negative emotion into integral and incidental components using a modern motivation-based framework, and assessed whether the former could change conflict adaptation. In the first experiment, we manipulated the duration of the inter-trial-interval to assess the actual time-scale of this effect. Integral negative emotion was induced by using loss-related feedback contingent on task performance, (...) and measured at the subjective and physiological levels. Results showed that conflict-driven adaptive control was enhanced when integral negative emotion was elicited, compared to a control condition without changes in defensive motivation. Importantly, this effect was only found when a short, as opposed to long ITI was used, suggesting that it had a short time scale. In the second experiment, we controlled for effe... (shrink)

In order to reduce the dimensionality of parameter space and enhance out-of-sample forecasting performance, this research compares regularization techniques with Autometrics in time-series modeling. We mainly focus on comparing weighted lag adaptive LASSO with Autometrics, but as a benchmark, we estimate other popular regularization methods LASSO, AdaLASSO, SCAD, and MCP. For analytical comparison, we implement Monte Carlo simulation and assess the performance of these techniques in terms of out-of-sample Root Mean Square Error, Gauge, and Potency. The comparison is assessed with (...) varying autocorrelation coefficients and sample sizes. The simulation experiment indicates that, compared to Autometrics and other regularization approaches, the WLAdaLASSO outperforms the others in covariate selection and forecasting, especially when there is a greater linear dependency between predictors. In contrast, the computational efficiency of Autometrics decreases with a strong linear dependency between predictors. However, under the large sample and weak linear dependency between predictors, the Autometrics potency ⟶ 1 and gauge ⟶ α. In contrast, LASSO, AdaLASSO, SCAD, and MCP select more covariates and possess higher RMSE than Autometrics and WLAdaLASSO. To compare the considered techniques, we made the Generalized Unidentified Model for covariate selection and out-of-sample forecasting for the trade balance of Pakistan. We train the model on 1985–2015 observations and 2016–2020 observations as test data for the out-of-sample forecast. (shrink)

This article investigates an adaptive neural network control algorithm for marine surface vessels with time-varying output constraints and unknown external disturbances. The nonlinear state-dependent transformation is introduced to eliminate the feasibility conditions of virtual controller. Moreover, the barrier Lyapunov function is used to achieve time-varying output constraints. As an important approximation tool, the NN is employed to approximate uncertain and continuous functions. Subsequently, the disturbance observer is structured to observe time-varying constraints and unknown external disturbances. The novel strategy can guarantee (...) that all signals in the closed-loop system are semiglobally uniformly ultimately bounded. Finally, the simulation results verify the benefit of the proposed method. (shrink)

This paper proposes a novel adaptive dynamic programming approach to address the optimal consensus control problem for discrete-time multiagent systems. Compared with the traditional optimal control algorithms for MASs, the proposed algorithm is designed on the basis of the event-triggered scheme which can save the communication and computation resources. First, the consensus tracking problem is transferred into the input-state stable problem. Based on this, the event-triggered condition for each agent is designed and the event-triggered ADP is presented. Second, neural networks (...) are introduced to simplify the application of the proposed algorithm. Third, the stability analysis of the MASs under the event-triggered conditions is provided and the estimate errors of the neural networks’ weights are also proved to be ultimately uniformly bounded. Finally, the simulation results demonstrate the effectiveness of the event-triggered ADP consensus control method. (shrink)

Children and adults use established global knowledge to generate real‐time linguistic predictions, but less is known about how listeners generate predictions in circumstances that semantically conflict with long‐standing event knowledge. We explore these issues in adults and 5‐ to 10‐year‐old children using an eye‐tracked sentence comprehension task that tests real‐time activation of unexpected events that had been previously encountered in brief stories. Adults generated predictions for these previously unexpected events based on these discourse cues alone, whereas children overall did not (...) override their established global knowledge to generate expectations for semantically conflicting material; however, they do show an increased ability to integrate discourse cues to generate appropriate predictions for sentential endings. These results indicate that the ability to rapidly integrate and deploy semantically conflicting knowledge has a long developmental trajectory, with adult‐like patterns not emerging until later in childhood. (shrink)

Much has been written about the need for trustworthy artificial intelligence (AI), but the underlying meaning of trust and trustworthiness can vary or be used in confusing ways. It is not always clear whether individuals are speaking of a technology’s trustworthiness, a developer’s trustworthiness, or simply of gaining the trust of users by any means. In sociotechnical circles, trustworthiness is often used as a proxy for ‘the good’, illustrating the moral heights to which technologies and developers ought to aspire, at (...) times with a multitude of diverse requirements; or at other times, no specification at all. In philosophical circles, there is doubt that the concept of trust should be applied at all to technologies rather than their human creators. Nevertheless, people continue to intuitively reason about trust in technologies in their everyday language. This qualitative study employed an empirical ethics methodology to address how developers and users define and construct requirements for trust throughout development and use, through a series of interviews. We found that different accounts of trust (rational, affective, credentialist, norms based, relational) served as the basis for individual granting of trust in technologies and operators. Ultimately, the most significant requirement for user trust and assessment of trustworthiness was the accountability of AI developers for the outputs of AI systems, hinging on the identification of accountable moral agents and perceived value alignment between the user and developer’s interests. (shrink)

We present three rights-based approaches to research and policies on gender justice and equity in the context of climate change adaptation. After a short introduction, we describe the dominant discourse that frames climate change and provide an overview of the literature that has depicted women both as vulnerable victims of climatic change and as active agents in adaptive responses. Discussion follows on the shift from gendered impacts to gendered adaptive capacities and embodied experiences, highlighting the continuing impact of social (...) biases and institutional practices that shape unequal access to and control over household and community decision-making processes undermining timely, fair, and successful adaptive responses. Assessment of rights-based frameworks considers the space they provide in addressing persistent gender and other inequalities, at different political and operational scales. We argue that a human security framework is useful to fill the gap in current gender and climate justice work, particularly when implemented through the entry point of adaptive social protection. Gender justice in climate change adaptation is an obligation for transformational social change, not just rights. The time is ripe to replace narrow-minded vulnerability studies with a contextualized understanding of our mutual fragility and a commitment to enhanced livelihood resilience, worldwide. (shrink)