Type theory in human-like learning and inference

Humans can generate reasonable answers to novel queries (Schulz, 2012): if I asked you what kind of food you want to eat for lunch, you would respond with a food, not a time. The thought that one would respond "After 4pm" to "What would you like to eat" is either a joke or a mistake, and seriously entertaining it as a lunch option would likely never happen in the first place. While understanding how people come up with new ideas, thoughts, explanations, and hypotheses that obey the basic constraints of a novel search space is of central importance to cognitive science, there is no agreed-on formal model for this kind of reasoning. We propose that a core component of any such reasoning system is a type theory: a formal imposition of structure on the kinds of computations an agent can perform, and how they're performed. We motivate this proposal with three empirical observations: adaptive constraints on learning and inference (i.e. generating reasonable hypotheses), how people draw distinctions between improbability and impossibility, and people's ability to reason about things at varying levels of abstraction.Comment: 5 pages, 0 figures, accepted into Beyond Bayes ICML '2

Analysis of Differential Gene Expression by Boolean Selection: Identification of Transcripts Associated with the Formation and Reorganization of Neuronal Networks.

The quantitative comparison of gene expression represents one of the major approaches for the analysis of gene function. Recently, the discovery of unknown genes based only upon their expression pattern has become possible through the application of various differential cloning methods, including subtractive hybridization, differential display, and expressed sequence tag analysis. Due to numerous technical and procedural limitations, however, none of these technologies is currently capable of rapidly identifying differentially regulated transcripts based on multiple expression-related criteria. Therefore, an alternative approach was devised which allows for the sequential application of numerous selection criteria during the initial screening process, thereby enabling the rapid identification of transcripts with highly specific expression patterns. Because of its use of multiple positive and negative selection steps, this approach is called Boolean selection. One of the first applications of this new approach was the search for novel genes associated with the formation and reorganization of neuronal networks in the mammalian brain. An ideal model system for this analysis is the retinocollicular system of the rat, where numerous aspects of neurite outgrowth, axon guidance, synapse formation and reorganization, and regulation of neuronal survival can easily be studied. Boolean selection was applied for the identification of transcripts preferentially expressed in the superior colliculus during late prenatal development as well as after the loss of afferent input in the adult animal. An initial analysis of several of these selected transcripts revealed that all satisfied at least one selection criterion and that over half satisfied both, indicating the usefulness of Boolean selection for the rapid identification of differentially regulated genes. Although additional analysis by in situ hybridization will still be necessary to verify the extent of differential expression and to provide information on the cellular localization of the transcripts identified so far, it was possible with this preliminary screen to gain new insight into some of the molecular and cellular activities in the superior colliculus during periods associated with the formation and reorganization of synaptic connections. Some of the identified transcripts encode proteins associated with post-transcriptional protein synthesis and modification events, including ribophorin (an essential subunit of the protein glycosylation complex ligosaccharyltransferase), calnexin (a membrane-associated molecular chaperone of the endoplasmic reticulum), and translation initiation factor, which together suggest enhanced levels of protein production and secretion. Other transcipts include rSec6 (part of the protein complex involved in the docking and fusion of synaptic vesicles to the plasma membrane) and Fyn (a nonreceptor tyrosine kinase found at high concentrations in axonal growth cones and also known be involved in synaptic plasticity), Fas-associated protein factor (a recently identified molecule potentially involved in Fas-mediated signal transduction during program m ed cell death), and a novel member of the EOF superfamily of transmembrane growth factors (which presently includes the EGF/TGFa family and the neuregulins). Further analysis of these molecules may provide additional information about the signaling mechanisms and cell-cell interactions at work during the establishment and modification of neuronal networks

VARIANCES: Life Unpercepted. Against Teleological Entrenchment in Evolution and Design Alike

In this work of foresight, I communicated my perception of Taleb's policy paper and the Black Swan problem discussed in it. To this effect, I: 1. Re-conceptualized the concept of "foresight,” non-teleologically, and its “method”; 2. Revived Empedocles’ non-teleological philosophy of evolution with modern scientific data; 3. Located the real GMO safety problem in (you guessed it) teleology: in the suppression of dissent within institutions under a seeming assumption of knowing what waste is. Keywords: the problem of induction, GMO, safety, evolution, horizontal gene transfer, innovation, innovators, imagination, opinion spread, public mistrust, the expert problem, falsification, aging, fragility, fragilizing, corruption, complexity, cooperation, waste, networks, systems, probability, emergence, Biosphere, Noosphere, cybernetics, policy, design, risk, strategy, foresight, genetic engineering, social constructionism, Semmelweis reflex, Neo-Darwinism, Protestant work ethics, fear of loss, fear of missing out, generation, efficiency, optimization, precaution, precautionary principle, induction, inclusion, dissent, groupthink, deduction, retroduction, cognition, cognitive cycle, propagation, complex systems engineering, monopoly, monoculture, decision-making, Moravec's paradox, Korzybski, Vernadsky, Nietzsche, Taleb, Galam, Hume, Lem, Margulis, general semantics, general systems theory, non-Aristotelian, time binding, networks, researchers, peer revie

A logical analysis of soft systems modelling: implications for information system design and knowledge based system design

The thesis undertakes an analysis of the modelling methods used in the Soft Systems Methodology (SSM) developed by Peter Checkland and Brian Wilson. The analysis is undertaken using formal logic and work drawn from modern Anglo-American analytical philosophy especially work in the area of philosophical logic, the theory of meaning, epistemology and the philosophy of science. The ability of SSM models to represent causation is found to be deficient and improved modelling techniques suitable for cause and effect analysis are developed. The notional status of SSM models is explained in terms of Wittgenstein's language game theory. Modal predicate logic is used to solve the problem of mapping notional models on to the real world. The thesis presents a method for extending SSM modelling in to a system for the design of a knowledge based system. This six stage method comprises: systems analysis, using SSM models; language creation, using logico-linguistic models; knowledge elicitation, using empirical models; knowledge representation, using modal predicate logic; codification, using Prolog; and verification using a type of non-monotonic logic. The resulting system is constructed in such a way that built in inductive hypotheses can be falsified, as in Karl Popper's philosophy of science, by particular facts. As the system can learn what is false it has some artificial intelligence capability. A variant of the method can be used for the design of other types of information system such as a relational database

The Routledge Handbook of Philosophy of Economics

The most fundamental questions of economics are often philosophical in nature, and philosophers have, since the very beginning of Western philosophy, asked many questions that current observers would identify as economic. The Routledge Handbook of Philosophy of Economics is an outstanding reference source for the key topics, problems, and debates at the intersection of philosophical and economic inquiry. It captures this field of countless exciting interconnections, affinities, and opportunities for cross-fertilization. Comprising 35 chapters by a diverse team of contributors from all over the globe, the Handbook is divided into eight sections: I. Rationality II. Cooperation and Interaction III. Methodology IV. Values V. Causality and Explanation VI. Experimentation and Simulation VII. Evidence VIII. Policy The volume is essential reading for students and researchers in economics and philosophy who are interested in exploring the interconnections between the two disciplines. It is also a valuable resource for those in related fields like political science, sociology, and the humanities.</p

ACHIEVING AUTONOMIC SERVICE ORIENTED ARCHITECTURE USING CASE BASED REASONING

Service-Oriented Architecture (SOA) enables composition of large and complex computational units out of the available atomic services. However, implementation of SOA, for its dynamic nature, could bring about challenges in terms of service discovery, service interaction, service composition, robustness, etc. In the near future, SOA will often need to dynamically re-configuring and re-organizing its topologies of interactions between the web services because of some unpredictable events, such as crashes or network problems, which will cause service unavailability. Complexity and dynamism of the current and future global network system require service architecture that is capable of autonomously changing its structure and functionality to meet dynamic changes in the requirements and environment with little human intervention. This then needs to motivate the research described throughout this thesis. In this thesis, the idea of introducing autonomy and adapting case-based reasoning into SOA in order to extend the intelligence and capability of SOA is contributed and elaborated. It is conducted by proposing architecture of an autonomic SOA framework based on case-based reasoning and the architectural considerations of autonomic computing paradigm. It is then followed by developing and analyzing formal models of the proposed architecture using Petri Net. The framework is also tested and analyzed through case studies, simulation, and prototype development. The case studies show feasibility to employing case-based reasoning and autonomic computing into SOA domain and the simulation results show believability that it would increase the intelligence, capability, usability and robustness of SOA. It was shown that SOA can be improved to cope with dynamic environment and services unavailability by incorporating case-based reasoning and autonomic computing paradigm to monitor and analyze events and service requests, then to plan and execute the appropriate actions using the knowledge stored in knowledge database

Embodied Decisions and the Predictive Brain

Decision-making has traditionally been modelled as a serial process, consisting of a number of distinct stages. The traditional account assumes that an agent first acquires the necessary perceptual evidence, by constructing a detailed inner repre- sentation of the environment, in order to deliberate over a set of possible options. Next, the agent considers her goals and beliefs, and subsequently commits to the best possible course of action. This process then repeats once the agent has learned from the consequences of her actions and subsequently updated her beliefs. Under this interpretation, the agent’s body is considered merely as a means to report the decision, or to acquire the relevant goods. However, embodied cognition argues that an agent’s body should be understood as a proper part of the decision-making pro- cess. Accepting this principle challenges a number of commonly held beliefs in the cognitive sciences, but may lead to a more unified account of decision-making. This thesis explores an embodied account of decision-making using a recent frame- work known as predictive processing. This framework has been proposed by some as a functional description of neural activity. However, if it is approached from an embodied perspective, it can also offer a novel account of decision-making that ex- tends the scope of our explanatory considerations out beyond the brain and the body. We explore work in the cognitive sciences that supports this view, and argue that decision theory can benefit from adopting an embodied and predictive perspective