On the adaptive advantage of always being right (even when one is not)

We propose another positive illusion – overconfidence in the generalisability of one’s theory – that fits with McKay & Dennett’s (M&D’s) criteria for adaptive misbeliefs. This illusion is pervasive in adult reasoning but we focus on its prevalence in children’s developing theories. It is a strongly held conviction arising from normal functioning of the doxastic system that confers adaptive advantage on the individual

Conflating Abstraction with Empirical Observation: The False Mind-Matter Dichotomy

\u3e Context • The alleged dichotomy between mind and matter is pervasive. Therefore, the attempt to explain mat- ter in terms of mind (idealism) is often considered a mirror image of that of explaining mind in terms of mat- ter (mainstream physicalism), in the sense of being structurally equivalent despite being reversely arranged. \u3e Problem • I argue that this is an error arising from language artifacts, for dichotomies must reside in the same level of abstraction. \u3e Method • I show that, because matter outside mind is not an empirical observation but rather an explanatory model, the epistemic symmetry between the two is broken. Consequently, matter and mind cannot reside in the same level of abstraction. \u3e Results • It then becomes clear that attempting to explain mind in terms of matter is epistemically more costly than attempting to explain matter in terms of mind. \u3e Implications • The qualities of experience are suggested to be not only epistemically, but also ontologically primary. \u3e Constructivist content • I high- light the primacy of perceptual constructs over explanatory abstraction on both epistemic and ontic levels. \u3e Key words • Idealism, physicalism, pancomputationalism, anti-realism, hard problem of consciousness, epistemic symmetry, explanatory abstraction, levels of abstraction

On the Online Generation of Effective Macro-operators

Macro-operator (“macro”, for short) generation is a well-known technique that is used to speed-up the planning process. Most published work on using macros in automated planning relies on an offline learning phase where training plans, that is, solutions of simple problems, are used to generate the macros. However, there might not always be a place to accommodate training. In this paper we propose OMA, an efficient method for generating useful macros without an offline learning phase, by utilising lessons learnt from existing macro learning techniques. Empirical evaluation with IPC benchmarks demonstrates performance improvement in a range of state-of-the-art planning engines, and provides insights into what macros can be generated without training

Looking for a psychology for the inner rational agent

Research in psychology and behavioural economics shows that individuals’ choices often depend on ‘irrelevant’ contextual factors. This presents problems for normative economics, which has traditionally used preference-satisfaction as its criterion. A common response is to claim that individuals have context-independent latent preferences which are ‘distorted’ by psychological factors, and that latent preferences should be respected. This response implicitly uses a model of human action in which each human being has an ‘inner rational agent’. I argue that this model is psychologically ungrounded. Although references to latent preferences appear in psychologically-based explanations of context-dependent choice, latent preferences serve no explanatory purpose

Infinitives of affect and intersubjectivity : on the indexical interpretation of the Finnish independent infinitives

This article presents an analysis of the structure and use of the Finnish independent infinitives. Although typological studies have shown that syntactically independent non-finite constructions are widespread in many languages, the understanding of their semantic and intersubjective motivation is still in its early stages. The current paper aims to enrich the understanding of independent non-finite constructions by closely looking at free-standing infinitive constructions in spoken and written Finnish: it combines theoretical concepts of Cognitive Grammar with the methodological tools of Interactional Linguistics to explore the nature of independent infinitives as a resource for conceptualization and the intersubjective functions that it affords. The paper suggests that the fact that independent infinitives are grammatically ungrounded makes them useful in interactional and textual sequences involving affect display. As the indexical functions of infinitives can be explained from their own morphosyntactic and semantic characteristics, the paper makes the more general claim that there is no synchronic evidence that would support the assumption that such constructions ever evolved, via ellipsis, from finite constructions. Methodologically and theoretically, the paper advocates an approach that takes into account both the social and cognitive nature of language, and promotes the view that Cognitive Grammar offers a flexible, semantically rich starting point for the description of intersubjective meanings conveyed by grammar, when combined with the context-sensitive and microanalytical methodology of Interactional Linguistics.Peer reviewe

Realizable response matrices of multiterminal electrical, acoustic, and elastodynamic networks at a given frequency

We give a complete characterization of the possible response matrices at a fixed frequency of n-terminal electrical networks of inductors, capacitors, resistors and grounds, and of n-terminal discrete linear elastodynamic networks of springs and point masses, both in the three-dimensional case and in the two-dimensional case. Specifically we construct networks which realize any response matrix which is compatible with the known symmetry properties and thermodynamic constraints of response matrices. Due to a mathematical equivalence we also obtain a characterization of the response matrices of discrete acoustic networks.Comment: 22 pages, 5 figure

Nanoscale content-addressable memory

A combined content addressable memory device and memory interface is provided. The combined device and interface includes one or more one molecular wire crossbar memories having spaced-apart key nanowires, spaced-apart value nanowires adjacent to the key nanowires, and configurable switches between the key nanowires and the value nanowires. The combination further includes a key microwire-nanowire grid (key MNG) electrically connected to the spaced-apart key nanowires, and a value microwire-nanowire grid (value MNG) electrically connected to the spaced-apart value nanowires. A key or value MNGs selects multiple nanowires for a given key or value

The Internal Charge Evolution of Multilayered Materials Undergoing Mono-Energetic Electron Bombardment

The charging of multilayer materials as related to the charging of spacecraft is one of the primary concerns related to activities in the space environment. To understand how multilayer materials undergoing electron bombardment charge, an in-depth study of energy-dependent material properties must be undertaken. These properties include the electron penetration depth, secondary electron emission, charge transport and electrostatic discharge. By using energy dependent models of these properties, along with the geometry of the system, multilayer models can be developed to predict the time evolution of the internal charge distribution. Using these models, the net surface potential and the measurement of electrode currents can be used to extrapolate information about the internal charge distribution. The Utah State University Materials Physics Group, with the funding of NASA James Webb Space Telescope project, performed several tests to understand the charging of multilayer dielectrics in various configurations. By using the Surface Voltage Probe to measure the net surface potential, along with measured electrode currents, the internal charge distribution can be inferred by using the developed theory for multilayer materials. Because each scenario requires a unique analysis, the theory of multilayer charging for a multilayer dielectric is outlined for four configurations defined as (i) surface layer deposition with grounded conductive layer, (ii) surface deposition with ungrounded conductive layer, (iii) conductive layer deposition with grounded conductive layer, and (iv) conductive layer deposition with ungrounded conductive layer. The results for these tests are outlined along with the fits given by the predictive models. The results of the tests show that knowledge of the energy-dependent electronic properties of the material, the energy of the incident electrons and the geometry of the system are all vital to predict the outcome of the given scenario. It is shown that for multilayer materials with an ungrounded conductive layer, electrostatic discharge occurs after the material charges past the breakdown limits of the material. These results can help to design, construct, and model already deployed spacecraft to mitigate and prevent detrimental spacecraft charging effects

Fault Location in Grid Connected Ungrounded PV Systems Using Wavelets

Solar photovoltaic (PV) power has become one of the major sources of renewable energy worldwide. This thesis develops a wavelet-based fault location method for ungrounded PV farms based on pattern recognition of the high frequency transients due to switching frequencies in the system and which does not need any separate devices for fault location. The solar PV farm used for the simulation studies consists of a large number of PV modules connected to grid-connected inverters through ungrounded DC cables. Manufacturers report that about 1% of installed PV panels fail annually. Detecting phase to ground faults in ungrounded underground DC cables is also difficult and time consuming. Therefore, identifying ground faults is a significant problem in ungrounded PV systems because such earth faults do not provide sufficient fault currents for their detection and location during system operation. If such ground faults are not cleared quickly, a subsequent ground fault on the healthy phase will create a complete short-circuit in the system, which will cause a fire hazard and arc-flashing. Locating such faults with commonly used fault locators requires costly external high frequency signal generators, transducers, relays, and communication devices as well as generally longer lead times to find the fault. This thesis work proposes a novel fault location scheme that overcomes the shortcomings of the currently available methods. In this research, high frequency noise patterns are used to identify the fault location in an ungrounded PV farm. This high frequency noise is generated due to the switching transients of converters combined with parasitic capacitance of PV panels and cables. The pattern recognition approach, using discrete wavelet transform (DWT) multi-resolution analysis (MRA) and artificial neural networks (ANN), is utilized to investigate the proposed method for ungrounded grid integrated PV systems. Detailed time domain electromagnetic simulations of PV systems are done in a real-time environment and the results are analyzed to verify the performance of the fault locator. The fault locator uses a wavelet transform-based digital signal processing technique, which uses the high frequency patterns of the mid-point voltage signal of the converters to analyze the ground fault location. The Daubechies 10 (db10) wavelet and scale 11 are chosen as the appropriate mother wavelet function and decomposition level according to the characteristics of the noise waveform to give the proposed method better performance. In this study, norm values of the measured waveform at different frequency bands give unique features at different fault locations and are used as the feature vectors for pattern recognition. Then, the three-layer feed-forward ANN classifier, which can automatically classify the fault locations according to the extracted features, is investigated. The neural network is trained with the Levenberg-Marquardt back-propagation learning algorithm. The proposed fault locating scheme is tested and verified for different types of faults, such as ground and line-line faults at PV modules and cables of the ungrounded PV system. These faults are simulated in a real-time environment with a digital simulator and the data is then analyzed with wavelets in MATLAB. The test results show that the proposed method achieves 99.177% and 97.851% of fault location accuracy for different faults in DC cables and PV modules, respectively. Finally, the effectiveness and feasibility of the designed fault locator in real field applications is tested under varying fault impedance, power outputs, temperature, PV parasitic elements, and switching frequencies of the converters. The results demonstrate the proposed approach has very accurate and robust performance even with noisy measurements and changes in operating conditions

A quantum-dot heat engine operating close to the thermodynamic efficiency limits

Cyclical heat engines are a paradigm of classical thermodynamics, but are impractical for miniaturization because they rely on moving parts. A more recent concept is particle-exchange (PE) heat engines, which uses energy filtering to control a thermally driven particle flow between two heat reservoirs. As they do not require moving parts and can be realized in solid-state materials, they are suitable for low-power applications and miniaturization. It was predicted that PE engines could reach the same thermodynamically ideal efficiency limits as those accessible to cyclical engines, but this prediction has not been verified experimentally. Here, we demonstrate a PE heat engine based on a quantum dot (QD) embedded into a semiconductor nanowire. We directly measure the engine's steady-state electric power output and combine it with the calculated electronic heat flow to determine the electronic efficiency $\eta$. We find that at the maximum power conditions, $\eta$ is in agreement with the Curzon-Ahlborn efficiency and that the overall maximum $\eta$ is in excess of 70$\%$ of the Carnot efficiency while maintaining a finite power output. Our results demonstrate that thermoelectric power conversion can, in principle, be achieved close to the thermodynamic limits, with direct relevance for future hot-carrier photovoltaics, on-chip coolers or energy harvesters for quantum technologies