From Consciousness to Knowledge – The Explanatory Power of Revelation

Epistemology in philosophy of mind is a difficult endeavor. Those who believe that our phenomenal life is different from other domains suggest that self-knowledge about phenomenal properties is certain and therefore privileged. Usually, this so called privileged access is explained by the idea that we have direct access to our phenomenal life. This means, in contrast to perceptual knowledge, self-knowledge is non-inferential. It is widely believed that, this kind of directness involves two different senses: an epistemic sense and a metaphysical sense. Proponents of this view often claim that this is due to the fact that we are acquainted with our current experiences. The acquaintance thesis, therefore, is the backbone in justifying privileged access. Unfortunately the whole approach has a profound flaw. For the thesis to work, acquaintance has to be a genuine explanation. Since it is usually assumed that any knowledge relation between judgments and the corresponding objects are merely causal and contingent (e.g. in perception), the proponent of the privileged access view needs to show that acquaintance can do the job. In this thesis, however, I claim that the latter cannot be done. Based on considerations introduced by Levine, I conclude that this approach involves either the introduction of ontologically independent properties or a rather obscure knowledge relation. A proper explanation, however, cannot employ either of the two options. The acquaintance thesis is, therefore, bound to fail. Since the privileged access intuition seems to be vital to epistemology within the philosophy of mind, I will explore alternative justifications. After discussing a number of options, I will focus on the so called revelation thesis. This approach states that by simply having an experience with phenomenal properties, one is in the position to know the essence of those phenomenal properties. I will argue that, after finding a solution for the controversial essence claim, this thesis is a successful replacement explanation which maintains all the virtues of the acquaintance account without necessarily introducing ontologically independent properties or an obscure knowledge relation. The overall solution consists in qualifying the essence claim in the relevant sense, leaving us with an appropriate ontology for phenomenal properties. On the one hand, this avoids employing mysterious independent properties, since this ontological view is physicalist in nature. On the other hand, this approach has the right kind of structure to explain privileged self-knowledge of our phenomenal life. My final conclusion consists in the claim that the privileged access intuition is in fact veridical. It cannot, however, be justified by the popular acquaintance approach, but rather, is explainable by the controversial revelation thesis.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.