Daļas un veselumi Aristoteļa substances koncepcijās

Disertācijā "Daļas un veselumi Aristoteļa substances koncepcijā" autore parāda, ka vairāku 'daļas' un 'veseluma' nozīmju nošķīrums atrisina substances (οὐσία) vienības problēmu. Lai gan problēma un arī risinājums ir Aristoteļa, viņš šim jautājumam nevelta atsevišķu izklāstu. Disertācija piedāvā detalizētu substances vienības problēmas analīzi, izmantojot instrumentus, kas darināti, ņemot vērā Aristoteļa piezīmes par daļām un veselumiem, t. i., mereoloģiju (no μέρος – 'daļa'). Izpētes centrā ir salikta (sajūtama vai vieliska) substance. Autore aizstāv vairākus Aristoteļa pētniecībā strīdīgus apgalvojumus (uzskatu, ka daļas–veseluma attiecībai (part–whole relation) ir vairākas nozīmes, priekšstatu par veidolu un vielu kā par īstenām (proper) un reālām (real) daļām, veidola saliktību), kuri tiek pamatoti, aplūkojot Aristoteļa darbu korpusa fragmentus un iztirzājot dažādu komentētāju viedokļus. Atslēgas vārdi: Aristotelis, daļa, veselums, substanceThe dissertation "Parts and Wholes in Aristotle's Conception of Substance" shows that the distinction of several senses of 'part' and 'whole' solves the problem of unity of substance (οὐσία). Although both the problem and the solution are Aristotle's, he himself has not provided a separate exposition devoted specifically to this topic. The dissertation offers a dissection of the problem of unity of substance with instruments shaped by Aristotle's remarks on parts and wholes, i.e. mereology (from μέρος, 'part'). The investigation pertains to the composite (sensible or material) substance. The author has defended various claims that are controversial in Aristotelian scholarship (the plurality of the senses of the part–whole relation; the idea that form and matter are proper and real parts; the complexity of form), which have been unfolded by providing evidence in Aristotle's corpus and by discussing the views of various commentators. Keywords: Aristotle, part, whole, substanc

Good things come to those who weight: evidence integration and decision termination in human choices

Perceptual decision-making describes the processes by which sensory information is recognised, evaluated and combined before making a commitment to a course of action. The goal of this thesis is to understand the neural and computational mechanisms underlying human perceptual decisions. Good decisions are made when all the available evidence is taken into account, and allowed to influence choice in proportion to its reliability. The first experimental chapter describes a categorisation task employed to investigate how information is integrated and employed according to its reliability during sequential sampling. It is observed that humans weight information approximately optimally. A subsequent experiment involving electroencephalographic (EEG) recordings elucidates a neurobiologically plausible mechanism that could give rise to this effect. However, reliability-based evidence integration may only be possible in relatively simple decisions, when task demands are lower. Previous work investigating more challenging decisions has shown that when two alternatives are viewed in series, locally preferred alternatives are processed with higher gain (“selective integration”). Experiment 2 asks (at both the behavioural and neural level) whether this selective integration happens at the level of attributes - i.e. category A versus B - or features - i.e. sub-dimensions of each of the attributes. Finding that it occurs at the level of features, we discuss the optimality of this strategy. We show, interestingly, that whilst selective integration at the feature level is not harmful to performance, only attribute-level selectivity is actively beneficial in this context. In everyday settings, the choice to stop integrating evidence and commit is often determined by the agent, rather than an external deadline. Experiment 3 uses a self-paced categorisation task to investigate what factors predict when decisions are made. The results show that decisions and their latencies are described by a quasi-optimal model, that times commitment in a way that depends on the evidence consistency. We show that an approximation based on normalisation can account for these findings at the computational level. This model predicts neural signals observed in humans

A scientific exploration of scenario planning, thinking, and cognitive biases

Scenario planning, as a recognised practice, is approaching the better part of a century. In this time it has experienced broad application across various industries and, as of late, growing popularity as an academic discipline. In stark contrast to its prolific use in the field and academia, is the lack in scholarly work that brings verifiable and robust knowledge regarding the efficacy of the practice. In order to understand the impact of scenario planning interventions, it is first necessary to understand scenario thinking. The importance of investigating scenario thinking lies in the notion that scenario planning has less to do with forecasting (i.e. aiming for facts) and more to do with futures-thinking (i.e. working with perceptions). The mental models, experiences, and abilities of scenario teams largely dictate the efficacy of a scenario planning intervention. At this time, however, scenario thinking remains a black box. The present investigation, first, provides a discussion on how to understand scenario thinking. A gestalt perspective is offered, where discrete cognitive features are defined, which comprise the structure of scenario thinking. The motivation to this discussion is understanding the level(s) of influence scenario thinking may succumb to, in the face of changes to external information. Next, three higher-order cognitions (creative, causal, and evaluative thinking) are explored, in depth, and tested against the Intuitive Logics model of scenario planning to help determine i) the robustness of scenario planning against ii) the influence of the cognitive experience. A multi-attribute approach is taken, borrowing methods from cognitive psychology, behavioural economics, and management science. A form of the traditional framing manipulation is used to measure for biases in scenario thinking. Results suggest that even the smallest change in information can lead to several biasing effects across the tested cognitive features of scenario thinking. Understanding the nature of influences on scenario thinking helps reveal the efficacy of scenario planning for management and organisations.Scenario planning, as a recognised practice, is approaching the better part of a century. In this time it has experienced broad application across various industries and, as of late, growing popularity as an academic discipline. In stark contrast to its prolific use in the field and academia, is the lack in scholarly work that brings verifiable and robust knowledge regarding the efficacy of the practice. In order to understand the impact of scenario planning interventions, it is first necessary to understand scenario thinking. The importance of investigating scenario thinking lies in the notion that scenario planning has less to do with forecasting (i.e. aiming for facts) and more to do with futures-thinking (i.e. working with perceptions). The mental models, experiences, and abilities of scenario teams largely dictate the efficacy of a scenario planning intervention. At this time, however, scenario thinking remains a black box. The present investigation, first, provides a discussion on how to understand scenario thinking. A gestalt perspective is offered, where discrete cognitive features are defined, which comprise the structure of scenario thinking. The motivation to this discussion is understanding the level(s) of influence scenario thinking may succumb to, in the face of changes to external information. Next, three higher-order cognitions (creative, causal, and evaluative thinking) are explored, in depth, and tested against the Intuitive Logics model of scenario planning to help determine i) the robustness of scenario planning against ii) the influence of the cognitive experience. A multi-attribute approach is taken, borrowing methods from cognitive psychology, behavioural economics, and management science. A form of the traditional framing manipulation is used to measure for biases in scenario thinking. Results suggest that even the smallest change in information can lead to several biasing effects across the tested cognitive features of scenario thinking. Understanding the nature of influences on scenario thinking helps reveal the efficacy of scenario planning for management and organisations

Democracy and Analogy: The Practical Reality of Deliberative Politics

According to the deliberative view of democracy, the legitimacy of democratic politics is closely tied to whether the use of political power is accompanied by a process of rational deliberation among the citizenry and their representatives. Critics have questioned whether this level of deliberative capacity is even possible among modern citizenries--due to limitations of time, energy, and differential backgrounds--which therefore calls into question the very possibility of this type of democracy. In my dissertation, I counter this line of criticism, arguing that deliberative democrats and their critics have both idealized the wrong kind of citizen deliberation. Citizen deliberation should not be concerned with the indeterminate project of "translating" abstract democratic principles and values into everyday cases of political problem-solving. Instead, deliberation should take the form of analogy, just as we already find it in everyday politics and affairs. When ordinary citizens use analogies, they do not derive decisions from general principles or values, but they still reason nonetheless. Seen from this analogical perspective, deliberative democracy is already a practical reality to a large degree. When an election is on the horizon, a campaign season arises in which debates, forums, and "barstool" dialogues exponentially increase the amount of citizen deliberation. In these settings, citizens can readily be seen to be mapping analogous past candidates, elections, issues, and problems onto those currently on the ballot so as to reason about them. Consequently, analogical reasoning allows citizens to treat the majority rule mechanisms that proliferate in real politics as "deliberative outlets," which is to say, as catalysts of deliberation akin to the "creative outlets" that catalyze self-expression in the arts. While citizens may recognize majority rule mechanisms as catalysts of deliberation, many democratic theorists will hesitate to embrace this vision of the practical reality of deliberative politics. Isn't analogical reasoning too low in rigor to be placed at the heart of the deliberative ideal? I develop two arguments to explain the foundational role analogy plays in deliberation and to counter such critics. First, I draw on the explosion of research on analogical reasoning over the past two decades to show that it is far more rigorous and systematic than many suppose. Second, I argue that to the extent that citizen deliberation is concerned with rational planning, rather than just reasoning in general, analogical reasoning is logically superior. When we reason about what to do, we make plans that incorporate predictions about what is likely to ensue when a given course of action is selected. However, as soon as predictions enter into deliberation, its underlying logic changes as well. The reason for this change in logic is that as our probabilistic reasoning expands, the probability of its conclusions degenerates. Therefore, when assessing probabilities, we no longer should seek decisions derived from long, elegant chains of reasoning that connect our various options to generalities like values and principles. Instead, what we need is "short and sweet," or terse, humble lines of reasoning, which are more congruent with this form of deliberation. Thus, to the extent that democratic deliberation is involved in rational planning, it calls not for the elegant, deductive kind of reasoning idealized by proponents and critics of deliberative democracy alike. Instead, democratic deliberation calls for the "short and sweet," analogical kind of decision-making we associate with ordinary citizens already. After all, as research has shown, analogies are a much preferred and rigorous way by which even experts engage in probabilistic reasoning. By focusing on analogical reasoning, I therefore conclude that the practical reality of deliberative democracy should be recognized in ways that might ordinarily be dismissed

Model Checking Trust-based Multi-Agent Systems

Trust has been the focus of many research projects, both theoretical and practical, in the recent years, particularly in domains where open multi-agent technologies are applied (e.g., Internet-based markets, Information retrieval, etc.). The importance of trust in such domains arises mainly because it provides a social control that regulates the relationships and interactions among agents. Despite the growing number of various multi-agent applications, they still encounter many challenges in their formal modeling and the verification of agents’ behaviors. Many formalisms and approaches that facilitate the specifications of trust in Multi-Agent Systems (MASs) can be found in the literature. However, most of these approaches focus on the cognitive side of trust where the trusting entity is normally capable of exhibiting properties about beliefs, desires, and intentions. Hence, the trust is considered as a belief of an agent (the truster) involving ability and willingness of the trustee to perform some actions for the truster. Nevertheless, in open MASs, entities can join and leave the interactions at any time. This means MASs will actually provide no guarantee about the behavior of their agents, which makes the capability of reasoning about trust and checking the existence of untrusted computations highly desired. This thesis aims to address the problem of modeling and verifying at design time trust in MASs by (1) considering a cognitive-independent view of trust where trust ingredients are seen from a non-epistemic angle, (2) introducing a logical language named Trust Computation Tree Logic (TCTL), which extends CTL with preconditional, conditional, and graded trust operators along with a set of reasoning postulates in order to explore its capabilities, (3) proposing a new accessibility relation which is needed to define the semantics of the trust modal operators. This accessibility relation is defined so that it captures the intuition of trust while being easily computable, (4) investigating the most intuitive and efficient algorithm for computing the trust set by developing, implementing, and experimenting different model checking techniques in order to compare between them in terms of memory consumption, efficiency, and scalability with regard to the number of considered agents, (5) evaluating the performance of the model checking techniques by analyzing the time and space complexity. The approach has been applied to different application domains to evaluate its computational performance and scalability. The obtained results reveal the effectiveness of the proposed approach, making it a promising methodology in practice

The Original Position and Justification

Master'sMASTER OF ART

Analysing the discourse on corruption in presidential speeches in Nigeria, 1957- 2015: Systemic functional linguistics and critical discourse analysis frameworks

Philosophiae Doctor - PhDCorruption as a concept is viewed differently by various disciplines, but there seems to be consensus that it relates to the misuse of public office for private gain. Studies in the social sciences, mainly political science, economics, sociology and law, have provided valuable insights into the subject, for example, its causes, manifestations and consequences. In a country such as Nigeria, corruption is said to have cost the country up to $20 trillion between 1960 and 2005, and it could cost up to 37% of its GDP by 2030 if the situation is not urgently addressed. The paradox, however, is that although all successive leaders of the country have consistently articulated their anti-corruption posture in national speeches, they get accused by their successors of not being tough on corruption both in word and in deed. Regrettably, there have been relatively few close textual analyses of presidential speeches carried out within analytical frameworks in linguistics that have the potential of revealing how presidents can simultaneously talk tough and soft on corruption, a contradiction that could well explain the putative anti-corruption posture of the country’s leaders and the ever deepening corruption in the land. It is against this backdrop that this study draws on Critical Discourse Analysis (CDA) and Systemic Functional Linguistics (SFL) in order to examine language choices related to the theme of corruption in speeches made by Nigerian presidents from 1957 to 2015. The objectives of the study are to (1) provide an overview of how the discourse on corruption has evolved in Nigerian presidential speeches from 1957-2015; (2) determine specific facets of the construal of corruption from the dominant choices made from the system of transitivity (process, participants, circumstance) in speeches by different presidents and at different time points in their tenure in office; (3) analyse how the interpersonal metafunction of language is enacted in the speeches by the presidents through the system of appraisal for a strategy of positive self-presentation and negative other-presentation; (4) interrogate from a critical discourse analysis standpoint the interest, ideological, partisan or other bases for the choices made in the speeches from the systems associated with the experiential and interpersonal metafunctions of language; and (5) to evaluate the different presidents in terms of how the above analyses position them in relation to combating corruption

Dissecting Discrimination

This Open-Access-book examines the phenomenon of discrimination using a descriptive approach. Discrimination is omnipresent, whether it is people who discriminate against other people or, more recently, also machines that discriminate against people. The first part of the analysis employs decision theory on discrimination, leading to two fundamental subtypes: taste-based discrimination and statistical discrimination. The second part links taste-based discrimination to social identity theory, demonstrates that not all taste-based discrimination is ultimately statistical discrimination, and reveals the evolutionary origins of our tastes. The third part surveys how people get their beliefs for statistical discrimination and thereby shows that they often deviate from Bayesianism: they have inherent prior beliefs and do not exclusively update their beliefs according to Bayes’ law. Additionally, the analysis of belief formation highlights the importance of the learning environment. The last part reassembles the previously dissected aspects of discrimination, presents a new descriptive model of discrimination, and lists five implications for a normative theory of discrimination