129 research outputs found

    Genetic algorithms with DNN-based trainable crossover as an example of partial specialization of general search

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    Universal induction relies on some general search procedure that is doomed to be inefficient. One possibility to achieve both generality and efficiency is to specialize this procedure w.r.t. any given narrow task. However, complete specialization that implies direct mapping from the task parameters to solutions (discriminative models) without search is not always possible. In this paper, partial specialization of general search is considered in the form of genetic algorithms (GAs) with a specialized crossover operator. We perform a feasibility study of this idea implementing such an operator in the form of a deep feedforward neural network. GAs with trainable crossover operators are compared with the result of complete specialization, which is also represented as a deep neural network. Experimental results show that specialized GAs can be more efficient than both general GAs and discriminative models.Comment: AGI 2017 procedding, The final publication is available at link.springer.co

    MizAR 60 for Mizar 50

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    As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically proves about 60% of the Mizar theorems in the hammer setting. We also automatically prove 75% of the Mizar theorems when the automated provers are helped by using only the premises used in the human-written Mizar proofs. We describe the methods and large-scale experiments leading to these results. This includes in particular the E and Vampire provers, their ENIGMA and Deepire learning modifications, a number of learning-based premise selection methods, and the incremental loop that interleaves growing a corpus of millions of ATP proofs with training increasingly strong AI/TP systems on them. We also present a selection of Mizar problems that were proved automatically

    AGI and the Knight-Darwin Law: why idealized AGI reproduction requires collaboration

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    Can an AGI create a more intelligent AGI? Under idealized assumptions, for a certain theoretical type of intelligence, our answer is: “Not without outside help”. This is a paper on the mathematical structure of AGI populations when parent AGIs create child AGIs. We argue that such populations satisfy a certain biological law. Motivated by observations of sexual reproduction in seemingly-asexual species, the Knight-Darwin Law states that it is impossible for one organism to asexually produce another, which asexually produces another, and so on forever: that any sequence of organisms (each one a child of the previous) must contain occasional multi-parent organisms, or must terminate. By proving that a certain measure (arguably an intelligence measure) decreases when an idealized parent AGI single-handedly creates a child AGI, we argue that a similar Law holds for AGIs

    Method for Reading Sensors and Controlling Actuators Using Audio Interfaces of Mobile Devices

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    This article presents a novel closed loop control architecture based on audio channels of several types of computing devices, such as mobile phones and tablet computers, but not restricted to them. The communication is based on an audio interface that relies on the exchange of audio tones, allowing sensors to be read and actuators to be controlled. As an application example, the presented technique is used to build a low cost mobile robot, but the system can also be used in a variety of mechatronics applications and sensor networks, where smartphones are the basic building blocks

    An examination of the factorial and convergent validity of four measures of conspiracist ideation, with recommendations for researchers

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    A number scales have been developed to measure conspiracist ideation, but little attention has been paid to the factorial validity of these scales. We reassessed the psychometric properties of four widely-used scales, namely the Belief in Conspiracy Theories Inventory (BCTI), the Conspiracy Mentality Questionnaire (CMQ), the Generic Conspiracist Beliefs Scale (GCBS), and the One-Item Conspiracy Measure (OICM). Eight-hundred-and-three U. S. adults completed all measures, along with measures of endorsement of 9/11 and anti- vaccination conspiracy theories. Through both exploratory and confirmatory factor analysis, we found that only the BCTI had acceptable factorial validity. We failed to confirm the factor structures of the CMQ and the GBCS, suggesting these measures had poor factorial valid- ity. Indices of convergent validity were acceptable for the BCTI, but weaker for the other measures. Based on these findings, we provide suggestions for the future refinement in the measurement of conspiracist ideation

    How young adults in London experience the Clubhouse Model of mental health recovery: a thematic analysis

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    Clubhouses are recovery orientated, participatory communities in which people with mental health diagnoses can take part in the running of the clubhouse. The objective of this research was to produce the first qualitative study of its kind, examining how the clubhouse model of mental health recovery is perceived and experienced by young adults aged 16-25. Five participants provided lengthy and detailed semi-structured interviews regarding their experiences as members of a clubhouse in London. Analysis produced themes including mixed age services as a distinct benefit, the benefits of getting involved in the work of the clubhouse, the mostly positive perception of the clubhouse compared with other mental health services, and the sense of personal change and social improvement experienced on becoming members of the clubhouse. While further research is needed, it was concluded that the clubhouse model was beneficial to all its young members, for reasons including its entirely collaborative and consultative process between staff and members, its humanitarian approach, its lack of rigid or inflexible time limits, and its reciprocal relationships, where members are expected to both provide and receive support

    Doing it for us: community identification predicts willingness to receive a COVID‐19 vaccination via perceived sense of duty to the community

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    The COVID-19 pandemic has presented huge challenges for communities across the world. Vaccines offer the best hope for controlling its deleterious effects, but not everybody is willing to be vaccinated, so it is important to explore variables that might predict vaccination willingness. The present study addressed this by drawing upon the Social Identity Approach, which posits that people’s membership of social groups is consequential for their thoughts and behaviour. Specifically, it was predicted that people’s strength of identification with their local community (a social group that came to particular prominence during the pandemic) would positively predict their willingness to engage in community-related prosocial normative behaviour (i.e., their perceived sense of duty, as a community member, to get vaccinated), and that this, in turn, would predict higher levels of vaccination willingness. Participants (N = 130) completed an online survey, which supported the hypothesised mediation model, even after controlling for subjective neighbourhood socio-economic status and age (two variables that are particularly likely to impact upon vaccination willingness). To our knowledge, this is the first study to apply Social Identity Approach principles to the study of COVID-19 vaccination willingness. The implications of the findings for governments’ efforts to boost vaccine uptake are discussed. Please refer to the Supplementary Material section to find this article’s Community and Social Impact Statement

    Intention Seekers: Conspiracist Ideation and Biased Attributions of Intentionality

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    Conspiracist beliefs are widespread and potentially hazardous. A growing body of research suggests that cognitive biases may play a role in endorsement of conspiracy theories. The current research examines the novel hypothesis that individuals who are biased towards inferring intentional explanations for ambiguous actions are more likely to endorse conspiracy theories, which portray events as the exclusive product of intentional agency. Study 1 replicated a previously observed relationship between conspiracist ideation and individual differences in anthropomorphisation. Studies 2 and 3 report a relationship between conspiracism and inferences of intentionality for imagined ambiguous events. Additionally, Study 3 again found conspiracist ideation to be predicted by individual differences in anthropomorphism. Contrary to expectations, however, the relationship was not mediated by the intentionality bias. The findings are discussed in terms of a domain-general intentionality bias making conspiracy theories appear particularly plausible. Alternative explanations are suggested for the association between conspiracism and anthropomorphism

    The synthetic psychology of the self

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    Synthetic psychology describes the approach of “understanding through building” applied to the human condition. In this chapter, we consider the specific challenge of synthesizing a robot “sense of self”. Our starting hypothesis is that the human self is brought into being by the activity of a set of transient self-processes instantiated by the brain and body. We propose that we can synthesize a robot self by developing equivalent sub-systems within an integrated biomimetic cognitive architecture for a humanoid robot. We begin the chapter by motivating this work in the context of the criteria for recognizing other minds, and the challenge of benchmarking artificial intelligence against human, and conclude by describing efforts to create a sense of self for the iCub humanoid robot that has ecological, temporally-extended, interpersonal and narrative components set within a multi-layered model of mind
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