Belief in free will as an adaptive,ungrounded belief

False beliefs and delusions are usually regarded negatively, especially in psychology and evolutionary biology. Recently, McKay and Dennett (2009b) have argued that there are ungrounded beliefs which confer benefits on individuals even if they are false. I propose to expand this class of beliefs to include the belief that one has free will, and I will defend the claim that this belief is advantageous, even if it is false. One derives one’s belief in control from one’s experience of control, which is generated by a set of cognitive systems termed “control systems.” While the control systems and the interpretive mechanism are useful in and of themselves, the belief in personal free will is adaptive because it directly leads to fitness-increasing behaviors. As such, we have good reason to regard the belief that one has free will as an adaptive, ungrounded belief. This paper will also suggest that further research on the possible distinction between belief in personal free will and belief in general free will may put us in a better position to understand recent, apparently contradictory data on individuals’ beliefs regarding free will and other related phenomena.     

Cumulative neurological factors associated with long-term outcomes in adult survivors of childhood brain tumors

Prior research has demonstrated the reliability and validity of the Neurological Predictor Scale (NPS) in relation to childhood brain tumor survivor outcomes; however, its use has not been examined in adult long-term survivors. The current study examines the concurrent validity of the NPS with long-term intellectual and adaptive outcomes in adult survivors of childhood brain tumors relative to individual variables alone. A total of 68 adult survivors of childhood brain tumors (M = 24 years old, SD = 4) almost 16 years post diagnosis (SD = 6) completed intellectual evaluations using the Wechsler Abbreviated Scale of Intelligence (WASI). Survivors’ adaptive functioning skills were assessed via informant structured clinical interviews (SIB-R). NPS scores were computed from data acquired from medical records. The NPS was significantly associated with intellectual (R² = 0.208, p < .05) and adaptive outcomes (R² = 0.30, p < .05) over and above individual risk factors. Approximately 18% of long-term survivors were identified as impaired in intellectual outcomes, and 29% were identified as impaired in adaptive functioning in everyday life skills. The NPS quantifies the cumulative effects of treatment and neurological sequelae experienced by both short- and long-term survivors of childhood brain tumors. It is a useful and easy measure to employ in clinical research that focuses on quantifying the neurological risk factors associated with long-term intellectual and adaptive functioning outcomes in adult survivors of childhood brain tumors.     

Fit to last: Exploring the longevity of the survival processing effect

Mounting evidence indicates that processing items for their survival value produces superior recall compared to a number of other well-known memory-enhancing techniques, and that this mnemonic advantage remains up to 48 hours after encoding (Raymaekers et al., 2014 Raymaekers, L. H. C., Otgaar, H., &; Smeets, T. (2014). The longevity of adaptive memory: Evidence for the mnemonic advantages of survival processing 24 and 48 hours later. Memory, 22, 19–25. doi: 10.1080/09658211.2013.791321[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). However, little attention has been dedicated to the survival processing effect in location memory, which may represent a better test of adaptive memory than retrieval of verbal information. The current study aims to fill this gap by exploring the longevity of the survival processing effect with both word list (Experiment 1) and location-based (Experiment 2) stimuli. Participants rated target items using a single incidental encoding scenario, either Survival versus Pleasantness (word stimuli) or Survival versus Scavenger Hunt (location stimuli). They were then asked to complete a surprise recall task immediately after the ratings and a second recall task 96 hours later. The results demonstrated that, despite a general reduction in memory performance across time, the survival processing advantage was detected at both test times for both stimuli types. These findings provide further support for the survival processing effect and extend the observed effect duration for both word lists and location to 96 hours.     

The Undecidability of Propositional Adaptive Logic

We investigate and classify the notion of final derivability of two basic inconsistency-adaptive logics. Specifically, the maximal complexity of the set of final consequences of decidable sets of premises formulated in the language of propositional logic is described. Our results show that taking the consequences of a decidable propositional theory is a complicated operation. The set of final consequences according to either the Reliability Calculus or the Minimal Abnormality Calculus of a decidable propositional premise set is in general undecidable, and can be -complete. These classifications are exact. For first order theories even finite sets of premises can generate such consequence sets in either calculus.     

Adaptive non-interventional heuristics for covariation detection in causal induction: model comparison and rational analysis

In this article, 41 models of covariation detection from 2 × 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi-coefficient under an extreme rarity assumption, which has been shown to be an important factor in covariation detection (McKenzie & Mikkelsen, 2007) and data selection (Hattori, 2002; Oaksford & Chater, 1994, 2003). The results were supportive of the new model. To investigate its explanatory adequacy, a rational analysis using two computer simulations was conducted. These simulations revealed the environmental conditions and the memory restrictions under which the new model best approximates the normative model of covariation detection in these tasks. They thus demonstrated the adaptive rationality of the new model.     

High capacity adaptive image steganography with cover region selection using dual-tree complex wavelet transform

The importance of image steganography is unquestionable in the field of secure multimedia communication. Imperceptibility and high payload capacity are some of the crucial parts of any mode of steganography. The proposed work is an attempt to modify the edge-based image steganography which provides higher payload capacity and imperceptibility by making use of machine learning techniques. The approach uses an adaptive embedding process over Dual-Tree Complex Wavelet Transform (DT-CWT) subband coefficients. Machine learning based optimization techniques are employed here to embed the secret data over optimal cover-image-blocks with minimal retrieval error. The embedding process will create a unique secret key which is imperative for the retrieval of data and need to be transmitted to the receiver side via a secure channel. This enhances the security concerns and avoids data hacking by intruders. The algorithm performance is evaluated with standard benchmark parameters like PSNR, SSIM, CF, Retrieval error, BPP and Histogram. The results of the proposed method show the stego-image with PSNR above 50 dB even with a dense embedding of up to 7.87 BPP. This clearly indicates that the proposed work surpasses the state-of-the-art image steganographic systems significantly.     

Extending adaptive world modeling by identifying and handling insufficient knowledge models

Adaptive knowledge modeling is an approach for extending the abilities of the Object-Oriented World Model, a system for representing the state of an observed real-world environment, to open-world modeling. In open environments, entities unforeseen at the design-time of a world model can occur. For coping with such circumstances, adaptive knowledge modeling is tasked with adapting the underlying knowledge model according to the environment. The approach is based on quantitative measures, introduced previously, for rating the quality of knowledge models. In this contribution, adaptive knowledge modeling is extended by measures for detecting the need for model adaptation and identifying the potential starting points of necessary model change as well as by an approach for applying such change. Being an extended and more detailed version of [17], the contribution also provides background information on the architecture of the Object-Oriented World Model and on the principles of adaptive knowledge modeling, as well as examination results for the proposed methods. In addition, a more complex scenario is used to evaluate the overall approach.     

Psychological well-being,life satisfaction,and self-esteem among adaptive perfectionists,maladaptive perfectionists,and nonperfectionists

Using a tripartite model of perfectionism and positive psychology framework, the present study examined patterns of psychological well-being, life satisfaction, and self-esteem across three groups: adaptive perfectionists, maladaptive perfectionists, and nonperfectionists. The participants were 200 college students in South Korea. Cluster analysis confirmed the existence of the three groups, mirroring findings from the previous literature. Adaptive perfectionists reported higher levels of environmental mastery and purpose in life of psychological well-being than nonperfectionists and maladaptive perfectionists. Adaptive perfectionists and nonperfectionists showed higher life satisfaction and self-esteem than maladaptive perfectionists; however, no significant differences between adaptive perfectionists and nonperfectionists were found on these variables. Implications of the findings and directions for future research are discussed.     

Learning and development of trust,acceptance and the mental model of ACC. A longitudinal on-road study

To harness the potential of advanced driver assistance systems, drivers must learn how to use them in a safe and appropriate manner. The present study investigates the learning process, as well as the development of trust, acceptance and the mental model for interacting with adaptive cruise control (ACC). Research questions aim to model the learning process in mathematical/statistical terms, examine moments and conditions when these processes stabilize, and assess how experience changes the mental model of the system. A sample of fifteen drivers without ACC experience drove a test vehicle with ACC ten consecutive times on the same route within a 2-month period. All participants were fully trained in ACC functionality by reading the owner’s manual in the beginning. Results show that learning, as well as the development of acceptance and trust in ACC follows the power law of learning. All processes stabilize at a relatively high level after the fifth session, which corresponds to 185 km or 3.5 h of driving. No decline is observable with ongoing system experience. However, limitations that are not experienced tend to disappear from the mental model if they are not activated by experience. Therefore, it is recommended that users be periodically reminded of system limitations (e.g. by intelligent tutoring systems) to make sure that corresponding knowledge nodes are activated.