Falk's hominin mother-infant model presupposes an emerging infant capacity to perceive and learn from afforded gestures and vocalizations. Unlike back-riding offspring of other primates, who were in no need to decenter their own body-centered perspective, a mirror neurons system may have been adapted in hominin infants to subserve the kind of (m)other-centered mirroring we now see manifested by human infants soon after birth.

The issue on the role of users in knowledge-based systems can be investigated from two aspects: the design aspect and the functionality aspect. Participatory design is an important approach for the first aspect while system adaptability supported by user modelling is crucial to the second aspect. In the article, we discuss the second aspect. We view a knowledge-based computer system as the partner of users' problem-solving process, and we argue that the system functionality can be enhanced (...) by adapting the behaviour of the system to fit the needs of users with different profiles. We emphasise that the notion of user modelling is crucial to realise such kind of flexibility. User modelling will be beneficial to the user, not only through adaptive interfaces, but also through the enhanced system adaptability. In a knowledge-based system, by incorporating user models, searching can be reduced to a smaller portion in the knowledge-base, thus enhancing system functionality. In other words, user modelling is incorporated to realise flexible inference control to achieve system adaptability. An example is provided, and a general conceptual model is sketched. We conclude this paper by emphasising that the design aspect and functionality aspect are complementary. Achieving enhanced functionality through joint efforts of computers and human users indicates a kind of participatory execution of computerised problem-solving or participatory problem-solving. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an (...) intelligent manner according to the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

In this paper, an adaptive fuzzy containment condtrol is considered for nonlinear multiagent systems, in which it contains the unknown control coefficient and actuator fault. The uncertain nonlinear function has been approximated by fuzzy logic system. The unknown control coefficient and the remaining control rate of actuator fault can be solved by introducing a Nussbaum function. In order to avoid the repeated differentiations of the virtual controllers, first-order filters are added to the traditional backstepping control method. By designing the (...) maximum norm of ideal adaptive parameters, only one adaptive parameter needs to be adjusted online for each agent itself. An adaptive fuzzy containment controller is constructed through the backstepping control technique and compensating signals. It is demonstrated that all the signals in nonlinear multiagent systems are bounded by designing adaptive fuzzy containment controller, and all followers can converge to the convex hull built by the leaders. The simulation studies can further confirm the effectiveness of the proposed control method in this paper. (shrink)

Computational functionalism [5] fails to understand the embodied and situated nature of behaviour by taking steady state functions as theoretical primitives, and by interpreting cognitive behaviour from a language-like, observer dependant framework without a naturalized normativity. Evolutionary functionalism [28, 27], on the other hand, by grounding functional normativity on historical processes fails to give an account of normative functionality based on the present causal mechanism producing behaviour. We propose an alternative autonomous dynamical framework where functionality is defined as contribution to (...) self-maintenance [15, 10, 35] and normativity as satisfaction of closure criteria. We develop this framework by a set of formal definitions in the framework of dynamical system theory and propose the hypothesis of an homeostatic-plasticity [31, 40] based general purpose value system as an internalized normative mechanism that selects between internal state trajectories to produce adaptive functionality under different environmental conditions. To test the hypothesis we develop a simulation model where lower level specifications of a control arquitecture (an homeostatic plastic DRNN) give rise (through a simulated evolutionary process) to adaptive behaviour in a foraging task where food sources can be poisonous or profitable. Analysis of the evolved agent show that plastic changes occur when the agent produces salient adaptive interactions, those plastic changes determining the adaptive strategy. The embodied and interactive adaptive functionality is dynamically analysed, illustrating the autonomous dynamical framework. (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)

In recent years, immune systems have sparked considerable interest within the philosophy of science. One issue that has received increased attention is whether other phyla besides vertebrates display an adaptive immune system. Particularly the discovery of CRISPR-Cas9-based systems has triggered a discussion about how to classify adaptive immune systems. One question that has not been addressed yet is the transgenerational aspect of the CRISPR-Cas9-based response. If immunity is acquired and inherited, how to distinguish evolutionary from immunological adaptation? To shed (...) light on this issue and obtain conceptual clarity, I will investigate the inheritance of small RNA responses to pathogens in the nematode C. elegans as a further potential instantiation of a transgenerational adaptive immune system. I will explore how to make sense of systems that lie at the crossroads between genetic, immunological, and evolutionary spheres and explore the consequences of a transgenerational perspective on immune systems for immunology and its philosophy. (shrink)

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)

The Cabin Pressure Control System is an essential part of the aviation environmental control system that ensures aircraft structure and flight crew safety. However, the CPCS usually has potential faults of sensors and actuators. To this end, a Simple Adaptive Control- based reconfiguration method is proposed to compensate for the above adverse effects. Some good pressure control performance of CPCS can be achieved by the basic pressure controller when the system is in normal operation. A parallel feedforward (...) compensator is designed to guarantee the closed-loop system’s stability and the almost strictly positive realness of the augmented system. Thus, the simple adaptive controller can be utilized for the CPCS. In particular, the reconfiguration system can update the control law online when the fault occurs without the system identification process. The reference model is obtained by mathematical model linearization after considering the mechanical characteristics of the CPCS. Extensive simulations under various typical fault scenarios are carried out throughout the entire flight envelope of the aircraft from take-off to landing. Simulation results validate the robustness and reconfiguration control capability of the proposed method. (shrink)

It is suggested that the control-system theory of Domjan et al. restates in engineering vocabulary the primary thesis of law-of-effect theories: namely, that classical-conditioning arrangements may involve CR-contingent reinforcement. The research cited by Domjan et al. is relevant to the idea that classical conditioning is an adaptive process, but is irrelevant to their control-system theory.

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)

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 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)

The vision of the new generation of office systems is based on the hypothesis that an automatic support system is all the more useful and acceptable, the more systems behaviour and performance are in accordance with features ofhuman behaviour. Consequently recent development activities are influenced by the paradigm of the computer as man's “cooperative assistant”. The metaphors ofassistance andcooperation illustrate some major requirements to be met by new office systems. Cooperative office systems will raise a set of new questions (...) about the future of human work, human-machine interaction, the forms of individual control of work, the scope of action and the development of competence in the frame of AI-supported cooperative work, the relative benefits of different types of organizations, etc. With increasing autonomy of the computer in task accomplishment, research should also be concerned with the question of the limits of such a development. In AI-research and development there is much discussion of the intended performance of that new technology. Perhaps this will provide insights into, how these new machines should support numerous aspects of individual or cooperative work. But we find fewer ideas about the future ofhuman work. What will the role of thehuman actor be in future AI-supported cooperative work? What kind of work do we want to support with AI-machines? In the following article I will try to identify some questions for further sociological research activities. I will base my considerations on some theoretical aspects ofunderstanding andmeaning. Regarding identical and non-identical aspects in communication behaviour of human and machines, I will focus on some questions to be investigated. Finally some methodological problems of sociological research in the field of Artificial Intelligence will be discussed, especially the so-called “Time-Dilemma” of sociological research in technology. (shrink)

Complex adaptive systems and nursingThere have been numerous references to complexity theory and complex systems in the recent healthcare literature, including nursing. However, exaggerated claims have (in my view) been made about how they can be applied to health service delivery, and there is a widespread tendency to misunderstand some of the concepts associated with complexity thinking (usually justified by describing the misconception as a metaphor). These conceptscanbe extended to systems and structures in healthcare organisations but, at this stage in (...) the development of complexity science, only in a modest and very cautious way. In this paper I first outline some of the key ideas in the theory of complex adaptive systems, and then suggest that they have been distorted by a series of influential articles in the medical literature. I go on to present a simple case study of my own and undertake a complexity analysis of it. In the conclusion I suggest that we should beware of some outdated ideas being trotted out in the guise of complexity — an exciting and diverse area of enquiry that those old ideas do not, in fact, resemble. (shrink)

This communique presents the Q-S synchronization of two nonidentical complex nonlinear hyperchaotic systems with unknown parameters. An adaptive controller based on adaptive integral sliding mode control and parameter update laws are designed to realize the synchronization and parameter identification to a given map vector. The aforementioned strategy’s employment demands the transformation of a system into a specific structure containing a nominal part and some unknown terms. An integral sliding mode controller is used to stabilize the error system by (...) designing nominal control accompanied by compensator control. For chattering suppression, a continuous compensator of smooth nature is used instead of conventional control. The stability of the proposed algorithm is established in an impressive way, using Lyapunov criteria. A numerical simulation is performed to illustrate the validity of the proposed synchronization scheme. (shrink)

Adaptation in Natural and Artificial Systems . J. H. Holland Cambridge, MA, Bradford/MIT Press, 1992.

Contemporary biological research has suggested that some host–microbiome multispecies systems (referred to as “holobionts”) can in certain circumstances evolve as unique biological individual, thus being a unit of selection in evolution. If this is so, then it is arguably the case that some biological adaptations have evolved at the level of the multispecies system, what we call hologenomic adaptations. However, no research has yet been devoted to investigating their nature, or how these adaptations can be distinguished from adaptations at (...) the species-level (genomic adaptations). In this paper, we cover this gap by investigating the nature of hologenomic adaptations. By drawing on the case of the evolution of sanguivory diet in vampire bats, we argue that a trait constitutes a hologenomic adaptation when its evolution can only be explained if the holobiont is considered the biological individual that manifests this adaptation, while the bacterial taxa that bear the trait are only opportunistic beneficiaries of it. We then use the philosophical notions of emergence and inter-identity to explain the nature of this form of individuality and argue why it is special of holobionts. Overall, our paper illustrates how the use of philosophical concepts can illuminate scientific discussions, in the trend of what has recently been called metaphysics of biology. (shrink)

The concept of “gradually adaptive frameworks” is introduced as a model with the potential to describe the evolution of belief evaluative systems through the consideration of reasonable arguments and evidence. This concept is demonstrated through an analysis of specific points of disagreement between David Elliott’s praxial philosophy and Bennett Reimer’s aesthetic philosophy. A parallel case of disagreement is introduced from the literature of contemporary epistemology. This case, comprised of a disagreement between Thomas Kelly and Richard Feldman, deals explicitly with the (...) subject of “peer disagreement”. The discussion of this conceptual analysis is used to establish an advocacy position for the central positioning of critical thinking skills in any educative endeavor. (shrink)

Recommender system depends on the thoughts of numerous users to predict the favourites of potential consumers. RS is vulnerable to malicious information. Unsuitable products can be offered to the user by injecting a few unscrupulous “shilling” profiles like push and nuke attacks into the RS. Injection of these attacks results in the wrong recommendation for a product. The aim of this research is to develop a framework that can be widely utilized to make excellent recommendations for sales growth. This (...) study uses the methodology that presents an enhanced clustering algorithm named as modified density peak clustering algorithm on the consumer review dataset to ensure a well-formed cluster. An improved recurrent neural network algorithm is proposed to detect these attacks in hybrid RS, which uses the content-based RS and collaborative filtering RS. The results are compared with other state of the art algorithms. The proposed method is more suitable for E-commerce applications where the number of customers and products grows rapidly. (shrink)

In this paper, an adaptive sliding mode control method based on neural networks is presented for a class of manipulator systems. The main characteristic of the discussed system is that the output variable is required to keep within a constraint set. In order to ensure that the system output meets the time-varying constraint condition, the asymmetric barrier Lyapunov function is selected in the design process. According to Lyapunov stability theory, the stability of the closed-loop system is analyzed. (...) It is demonstrated that all signals in the resulted system are bounded, the tracking error converges to a small compact set, and the system output limits in its constrained set. Finally, the simulation example is used to show the effectiveness of the presented control strategy. (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)

Nowadays, the power systems are getting more and more complicated because of the delays introduced by the communication networks. The existence of the delays usually leads to the degradation and/or instability of power system performance. On account of this point, the traditional load frequency control approach for power system sketches a destabilizing impact and an unacceptable system performance. Therefore, this paper proposes a new LFC based on adaptive integral second-order sliding mode control approach for the large-scale power (...) system with communication delays. First, a new linear matrix inequality is derived to ensure the stability of whole power systems using Lyapunov stability theory. Second, an AISOSMC law is designed to ensure the finite time reachability of the system states. To the best of our knowledge, this is the first time the AISOSMC is designed for LFC of the LSPSwCD. In addition, the report of testing results presents that the suggested LFC based on AISOSMC can not only decrease effectively the frequency variation but also make successfully less in mount of power oscillation/fluctuation in tie-line exchange. (shrink)

The development of new theory is often spurred by novel techniques that provide better answers to existing questions, or that allow asking new ones. In the field of strategy and organization science, models of complex adaptive systems have renewed theoretical work on a fundamental question: how organizations can adapt effectively to their environments. This article has three objectives: to highlight some areas where models of organizations as complex adaptive systems have made substantial contributions: the search for solutions to sets of (...) interdependent choices, the challenge of balancing processes of exploration and exploitation, and the organization of imperfect decision makers; to point to several challenges and tradeoffs which can limit the explanatory power and eventual impact of the modeling enterprise; and to sketch out possible future directions of research that would do further justice to the notion of organizations as complex adaptive systems. (shrink)

Since the foundation of the Santa Fe Institute, the new science of complex adaptive systems has seen extraordinary development, breaking with previous, more epistemological, trends in complexity theory. This article makes a critique of CAS as a model of the current global complexity. Its basic model, the cellular automaton, which focuses on the interactive dynamics among components, ignores the nature of any complex system as constructed by the observer/actor and is unable to explain the sociohistorical construction of the agents/subjects (...) and the social structure in which they are located, thus being unable to accurately represent the overall social complexity. (shrink)

A novel advantage of the use of machine learning (ML) systems in medicine is their potential to continue learning from new data after implementation in clinical practice. To date, considerations of the ethical questions raised by the design and use of adaptive machine learning systems in medicine have, for the most part, been confined to discussion of the so-called “update problem,” which concerns how regulators should approach systems whose performance and parameters continue to change even after they have received regulatory (...) approval. In this paper, we draw attention to a prior ethical question: whether the continuous learning that will occur in such systems after their initial deployment should be classified, and regulated, as medical research? We argue that there is a strong prima facie case that the use of continuous learning in medical ML systems should be categorized, and regulated, as research and that individuals whose treatment involves such systems should be treated as research subjects. (shrink)

As a class of familiar nonlinear systems, nonaffine systems are frequently encountered in practical applications. Currently, in the context of learning control, there is a lack of research results about such general class of nonlinear systems, especially for the case of performing infinite interval tasks. This article focuses on the incremental adaptive control for nonlinear systems in nonaffine form, without requiring periodicity or repeatability. Instead of using the integral adaptation, incremental adaptive mechanisms are developed and the corresponding control schemes are (...) presented, by which the numerical integration for implementation can be avoided. With the proposed incremental adaptation, the implicit function theorem is introduced to solve the intractability problem of the nonaffine structure. The robustness of the tracking error is characterized, with the aid of a proposed key lemma, while the boundedness of all the variables is examined. Numerical results are presented to verify the effectiveness of the proposed control design. (shrink)

Earthquake is a kind of natural disaster, which will have a great impact on the building structure. In the vibration control field of building structures, the timeliness of system stability is extremely important. In traditional control methods, the timeliness is not paid enough attention for systems with uncertain seismic waves. For setting this problem, fuzzy adaptive compensation control for uncertain building structural systems by sliding-mode technology is proposed. It is combined with fuzzy adaptive control and sliding-mode control to ensure (...) that the system can be stable with satisfied timeliness. Also, saturation function is used to ensure the feasible physical implementation of the control system. Compared with the traditional LQR control, the simulation results showed that the proposed method can make the system reach a stable state with rapid convergence performance and has a feasible physical implementation. (shrink)

Progress has become a suspect concept in evolutionary biology, not the least because the core concepts of neo-Darwinism do not support the idea that evolution is progressive. There have been a number of attempts to account for directionality in evolution through additions to the core hypotheses of neo-Darwinism, but they do not establish progressiveness, and they are somewhat of an ad hoc collection. The standard account of fitness and adaptation can be rephrased in terms of information theory. From this, an (...) information of adaptation can be defined in terms of a fitness function. The information of adaptation is a measure of the mutual information between biota and their environment. If the actual state of adaptation lags behind the state of optimal adaptation, then it is possible for the information of adaptation to increase indefinitely. Since adaptations are functional, this suggests the possibility of progressive evolution in the sense of increasing adaptation. Keywords: evolution, information, adaptation, fitness, entropy, progress.. (shrink)

Deformation of ground during tunnelling projects is one of the complex issues that is required to be monitored carefully to avoid the unexpected damages and human losses. Accurate prediction of ground settlement is a crucial concern for tunnelling problems, and the adequate predictive model can be a vital tool for tunnel designers to simulate the ground settlement accurately. This study proposes relatively new hybrid artificial intelligence models to predict the ground settlement of earth pressure balance shield tunnelling in the Bangkok (...) MRTA project. The predictive models were various nature-inspired frameworks, such as differential evolution, particle swarm optimization, genetic algorithm, and ant colony optimizer to tune the adaptive neuro-fuzzy inference system. To obtain the accurate and reliable results, the modeling procedure is established based on four different dataset scenarios including preprocessed and normalized, preprocessed and nonnormalized, non-preprocessed and normalized, and non-preprocessed and nonnormalized datasets. Results indicated that PPN dataset scenario significantly affected the prediction models in terms of their perdition accuracy. Among all the developed hybrid models, ANOFS-PSO model achieved the best predictability performance. In quantitative terms, PPN-ANFIS-PSO model attained the least root mean square error value of 7.98 and a correlation coefficient value of 0.83. Overall, the attained results confirmed the superiority of the explored hybrid AI models as robust predictive model for ground settlement of earth pressure balance shield tunnelling. (shrink)

This paper deals with designing a harvesting control strategy for a predator–prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for (...) unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy. (shrink)

In the complex environment, the suddenly changing structural parameters and abrupt actuator failures are often encountered, and the negligence or unproper handling method may induce undesired or unacceptable results. In this paper, taking the suddenly changing structural parameters and abrupt actuator failures into consideration, we focus on the robust adaptive control design for a class of heterogeneous Takagi–Sugeno fuzzy nonlinear systems subjected to discontinuous multiple uncertainties. The key point is that the switch modes not only vary with the system (...) time but also vary with the system states, and the intrinsic heterogeneous characteristics make it difficult to design stable controllers. Firstly, the concepts of differential inclusion are introduced to describe the heterogeneous fuzzy systems. Meanwhile, a fundamental lemma is provided to demonstrate the criteria of the boundness for a Filippov solution. Then, by using the set-valued Lie derivative of the Lyapunov function and introducing a vector of specific continuous functions, the closed-loop T-S fuzzy differential inclusion systems are proved to be ultimately bounded. The sufficient conditions for system stability are derived in term of linear matrix inequalities, which can be solved directly. Finally, a numerical example is provided to illustrate the effectiveness of the proposed control algorithm. (shrink)

The visual system adapts to a wide range of visual features, from lower-level features like color and motion to higher-level features like causality and, perhaps, number. According to some, adaptation is a strictly perceptual phenomenon, such that the presence of adaptation licenses the claim that a feature is truly perceptual in nature. Given the theoretical importance of claims about adaptation, then, it is important to understand exactly when the visual system does and does not exhibit adaptation. Here, we (...) take as a case study one specific kind of adaptation: visual adaptation to size. Supported by evidence from four experiments, we argue that, despite robust effects of size adaptation in the lab, (1) size adaptation effects are phenomenologically underwhelming (in some cases, hardly appreciable at all), (2) some effects of size adaptation appear contradictory, and difficult to explain given current theories of size adaptation, and (3) prior studies on size adaptation may have failed to isolate size as the adapted dimension. Ultimately, we argue that while there is evidence to license the claim that size adaptation is genuine, size adaptation is a puzzling and poorly understood phenomenon. (shrink)