Interactions between normative systems and software cognitive agents. A formalization in temporal modal defeasible logic and its implementation

Sustainable computer systems require some flexibility to adapt to environmental unpredictable changes. A solution lies in autonomous software agents which can adapt autonomously to their environments. Though autonomy allows agents to decide which behavior to adopt, a disadvantage is a lack of control, and as a side effect even untrustworthiness: we want to keep some control over such autonomous agents. How to control autonomous agents while respecting their autonomy? A solution is to regulate agents’ behavior by norms. The normative paradigm makes it possible to control autonomous agents while respecting their autonomy, limiting untrustworthiness and augmenting system compliance. It can also facilitate the design of the system, for example, by regulating the coordination among agents. However, an autonomous agent will follow norms or violate them in some conditions. What are the conditions in which a norm is binding upon an agent? While autonomy is regarded as the driving force behind the normative paradigm, cognitive agents provide a basis for modeling the bindingness of norms. In order to cope with the complexity of the modeling of cognitive agents and normative bindingness, we adopt an intentional stance. Since agents are embedded into a dynamic environment, things may not pass at the same instant. Accordingly, our cognitive model is extended to account for some temporal aspects. Special attention is given to the temporal peculiarities of the legal domain such as, among others, the time in force and the time in efficacy of provisions. Some types of normative modifications are also discussed in the framework. It is noteworthy that our temporal account of legal reasoning is integrated to our commonsense temporal account of cognition. As our intention is to build sustainable reasoning systems running unpredictable environment, we adopt a declarative representation of knowledge. A declarative representation of norms will make it easier to update their system representation, thus facilitating system maintenance; and to improve system transparency, thus easing system governance. Since agents are bounded and are embedded into unpredictable environments, and since conflicts may appear amongst mental states and norms, agent reasoning has to be defeasible, i.e. new pieces of information can invalidate formerly derivable conclusions. In this dissertation, our model is formalized into a non-monotonic logic, namely into a temporal modal defeasible logic, in order to account for the interactions between normative systems and software cognitive agents.

Integration of MFA and LCA methodologies: the anthropogenic aluminium cycle in Italy

MFA and LCA methodologies were applied to analyse the anthropogenic aluminium cycle in Italy with focus on historical evolution of stocks and flows of the metal, embodied GHG emissions, and potentials from recycling to provide key features to Italy for prioritizing industrial policy toward low-carbon technologies and materials. Historical trend series were collected from 1947 to 2009 and balanced with data from production, manufacturing and waste management of aluminium-containing products, using a ‘top-down’ approach to quantify the contemporary in-use stock of the metal, and helping to identify ‘applications where aluminium is not yet being recycled to its full potential and to identify present and future recycling flows’. The MFA results were used as a basis for the LCA aimed at evaluating the carbon footprint evolution, from primary and electrical energy, the smelting process and the transportation, embodied in the Italian aluminium. A discussion about how the main factors, according to the Kaya Identity equation, they did influence the Italian GHG emissions pattern over time, and which are the levers to mitigate it, it has been also reported. The contemporary anthropogenic reservoirs of aluminium was estimated at about 320 kg per capita, mainly embedded within the transportation and building and construction sectors. Cumulative in-use stock represents approximately 11 years of supply at current usage rates (about 20 Mt versus 1.7 Mt/year), and it would imply a potential of about 160 Mt of CO2eq emissions savings. A discussion of criticality related to aluminium waste recovery from the transportation and the containers and packaging sectors was also included in the study, providing an example for how MFA and LCA may support decision-making at sectorial or regional level. The research constitutes the first attempt of an integrated approach between MFA and LCA applied to the aluminium cycle in Italy.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Embodied computation and life: building blocks for open-ended evolution

Il presente lavoro si propone di sviluppare una analogia formale tra sistemi dinamici e teoria della computazione in relazione all’emergenza di proprietà biologiche da tali sistemi. Il primo capitolo sarà dedicato all’estensione della teoria delle macchine di Turing ad un più ampio contesto di funzioni computabili e debolmente computabili. Mostreremo quindi come un sistema dinamico continuo possa essere elaborato da una macchina computante, e come proprietà informative quali l’universalità possano essere naturalmente estese alla fisica attraverso questo ponte formale. Nel secondo capitolo applicheremo i risultati teorici derivati nel primo allo sviluppo di un sistema chimico che mostri tali proprietà di universalità, ponendo particolare attenzione alla plausibilità fisica di tale sistema.

Cognition and driving in older persons

In Switzerland, approximately 350,000 people aged 70 years or older own a valid driving license. By law, these drivers are medically assessed every other year, most commonly by their general practitioner, to exclude that a medical condition is interfering with their driving skills. A prerequisite for driving is the integration of high-level cognitive functions with perception and motor function. Ageing, per se, does not necessarily impair driving or increase the crash risk. However, medical conditions, such as cognitive impairment and dementia, become more prevalent with advancing age and may contribute to poor driving and an increased crash risk. The extent to which driving skills are impaired depends on the cause of dementia, disease severity, other co-morbidities and individual compensation strategies. Dementia often remains undiagnosed and therefore general practitioners (GPs) can find themselves in the difficult situation to disclose a suspicion about cognitive impairment and queries about medical fitness to drive, at the same time. In addition, the literature suggests that cognitive screening tests, most commonly used by GPs, have a limited role in judging whether an older person remains fit to drive. Further specialist assessment, for example in a memory clinic or on the road testing (ORT), may be helpful when the diagnosis or its implication for driving remain unclear. Here, we review the literature about cognition and driving, for GPs who advise older drivers who wish to continue driving.

Social Cognition And Functional Brain Imaging: Extending The Broader Autism Phenotype

Evidence suggests that the social cognition deficits prevalent in autism spectrum disorders (ASDs) are widely distributed in first degree and extended relatives. This ¿broader autism phenotype¿ (BAP) can be extended into non-clinical populations and show wide distributions of social behaviors such as empathy and social responsiveness ¿ with ASDs exhibiting these behaviors on the lower ends of the distributions. Little evidence has previously shown relationships between self-report measures of social cognition and more objective tasks such as face perception in functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). In this study, three specific hypotheses were addressed: a) increased social ability, as measured by an increased Empathy Quotient, decreased Social Responsiveness Scale (SRS-A) score, and increased Social Attribution Task score, will predict increased activation of the fusiform gyrus in response to faces as compared to houses; b) these same measures will predict N170 amplitude and latency showing decreased latency and increased amplitude for faces as compared to houses with increased social ability; c) increased amygdala volume will predict increased fusiform gyrus activation when viewing faces as compared to houses. Findings supported all of the hypotheses. Empathy scores significantly predicted both right FFG activation [F(1,20) = 4.811, p = .041, ß = .450, R2 = 0.20] and left FFG activation [F(1,20) = 7.70, p = .012, ß = .537, R2 = 0.29]. Based on ERP results increased right lateralization face-related N170 was significantly predicted by the EQ [F(1,54) = 6.94, p = .011, ß = .338, R2 = 0.11]. Finally, total amygdala volume significantly predicted right [F(1,20) = 7.217, p = .014, ß = .515, R2 = 0.27] and left [F(1,20) = 36.77, p < .001, ß = .805, R2 = 0.65] FFG activation. Consistent with the a priori hypotheses, traits attributed to the BAP can significantly predict neural responses to faces in a non-clinical population. This is consistent with the face processing deficits seen in ASDs. The findings presented here contribute to the extension of the BAP from unaffected relatives of individuals with ASDs to the general population. These findings also give continued evidence in support of a continuous distribution of traits found in psychiatric illnesses in place of a traditional, dichotomous ¿all-or-nothing¿ diagnostic framework of neurodevelopmental and neuropsychiatric disorders.

Social Cognition and Neural Substrates of Face Perception: Implications for Neurodevelopmental and Neuropsychiatric Disorders

BACKGROUND: Social cognition is an important aspect of social behavior in humans. Social cognitive deficits are associated with neurodevelopmental and neuropsychiatric disorders. In this study we examine the neural substrates of social cognition and face processing in a group of healthy young adults to examine the neural substrates of social cognition. METHODS: Fifty-seven undergraduates completed a battery of social cognition tasks and were assessed with electroencephalography (EEG) during a face-perception task. A subset (N=22) were administered a face-perception task during functional magnetic resonance imaging. RESULTS: Variance in the N170 EEG was predicted by social attribution performance and by a quantitative measure of empathy. Neurally, face processing was more bilateral in females than in males. Variance in fMRI voxel count in the face-sensitive fusiform gyrus was predicted by quantitative measures of social behavior, including the Social Responsiveness Scale (SRS) and the Empathizing Quotient. CONCLUSIONS: When measured as a quantitative trait, social behaviors in typical and pathological populations share common neural pathways. The results highlight the importance of viewing neurodevelopmental and neuropsychiatric disorders as spectrum phenomena that may be informed by studies of the normal distribution of relevant traits in the general population. Copyright 2014 Elsevier B.V. All rights reserved.

Investigation of Rudimentary Meta-Cognition in Lion-Tailed Macaques and Tufted Capuchins

Meta-cognition, or "thinking about thinking," has been studied extensively in humans, but very little is known about the process in animals. Although great apes and rhesus macaques (Macaca mulatta) have demonstrated multiple apparently meta-cognitive abilities, other species have either been largely ignored or failed to convincingly display meta-cognitive traits. Recent work by Marsh, however, raised the possibility that some species may possess rudimentary or partial forms of meta-cognition. This thesis sought to further investigate this possibility by running multiple comparative experiments. The goal of the first study was to examine whether lion-tailed macaques, a species that may have a rudimentary form of meta-cognition, are able to use an uncertainty response adaptively, and if so, whether they could use the response flexibly when the stimuli for which the subjects should be uncertain changed. The macaques' acquisition of the initial discrimination task is ongoing, and as such there were not yet data to support a conclusion either way. In the second study, tufted capuchins were required to locate a food reward hidden beneath inverted cups that sat on a Plexiglas tray. In some conditions the capuchins were shown where the food was hidden, in others they could infer its location, and in yet others they were not given information about the location of the food. On all trials, however, capuchins could optionally seek additional information by looking up through the Plexiglas into the cups. In general, capuchins did this less often when they were shown the food reward, but not when they could infer the reward's location. These data suggest capuchins only meta-cognitively control their information seeking in some conditions, and thus, add support to the potential for a rudimentary form of meta-cognition. In convergence with other studies, these results may represent early models for rudimentary meta-cognition, although viable alternative explanations still remain.

Social Cognition, Face Processing, and Oxytocin Receptor Single Nucleotide Polymorphisms in Typically Developing Children

Recent research has provided evidence of a link between behavioral measures of social cognition (SC) and neural and genetic correlates. Differences in face processing and variations in the oxytocin receptor (OXTR) gene have been associated with SC deficits and autism spectrum disorder (ASD) traits. Much work has examined the qualitative differences between those with ASD and typically developing (TD) individuals, but very little has been done to quantify the natural variation in ASD-like traits in the typical population. The present study examines this variation in TD children using a multidimensional perspective involving behavior assessment, neural electroencephalogram (EEG) testing, and OXTR genotyping. Children completed a series of neurocognitive assessments, provided saliva samples for sequencing, and completed a face processing task while connected to an EEG. No clear pattern emerged for EEG covariates or genotypes for individual OXTR single nucleotide polymorphisms (SNPs). However, SNPs rs2254298 and rs53576 consistently interacted such that the AG/GG allele combination of these SNPs was associated with poorer performance on neurocognitive measures. These results suggest that neither SNP in isolation is risk-conferring, but rather that the combination of rs2254298(A/G) and rs53576(G/G) confers a deleterious effect on SC across several neurocognitive measures. Copyright 2014. Published by Elsevier Ltd.