Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

Unexpected Aspects of Expectancy in Music: A Spreading Activation Explanation

A well agreed discourse in music perception research is that affective response can be generated by music when a tendency in the music is delayed or inhibited. There is a consensus that this tendency is statistically driven, derived from exposure to culturally situated musical idioms. By presenting a neural-network inspired spreading activation model (SAM) this paper argues that the nature of the tendency is worthy of further investigation. SAM organises the music stream perceived by the listener continuously into segments such that a match with an existing ‘mental representation’ (node) is found, which is then linked to the node for the previously segmented part of the music stream, with the link between these nodes strengthening and consolidating with exposure. The currently activated segment (the music being sounded) will prime the best matching (strongest linked) node available, generating expectancy. Expectancy is defined as the most strongly primed segment, and emerges dynamically through experience with environmental and musical contexts, rather than schematic or prototypical means. Expectancy is the specific exemplar instance that the activated (currently sounding) segment of music and contextual factors prime. This hypothesis of veridical dominance has implications for enduring aspects of music expectancy theory: (1) individual experiences matter in the formation of expectations; (2) expectations are a dynamic process, that change and are updated with experience; (3) context plays a critical role in expectancy; and (4) schema, prototypes and statistical accounts of expectation should be treated as convenient approximations of underlying cognitive processes

Proceedings of the KI 2009 Workshop on Complex Cognition

The KI ´09 workshop on Complex Cognition was a joint venture of the Cognition group of the Special Interest Group Artificial Intelligence of the German Computer Science Society (Gesellschaft für Informatik) and the German Cognitive Science Association. Dealing with complexity has become one of the great challenges for modern information societies. To reason and decide, plan and act in complex domains is no longer limited to highly specialized professionals in restricted areas such as medical diagnosis, controlling technical processes, or serious game playing. Complexity has reached everyday life and affects people in such mundane activities as buying a train ticket, investing money, or connecting a home desktop to the internet. Research in cognitive AI can contribute to supporting people navigating through the jungle of everyday reasoning, decision making, planning and acting by providing intelligent support technology. Lessons learned from expert systems research of the nineteen-eighties show that the aim should not be to provide for fully automated systems which can solve specialized tasks autonomously but instead to develop interactive assistant systems where user and system work together by taking advantage of the respective strengths of human and machine. To accomplish a smooth collaboration between humans and intelligent systems, basic research in cognition is a necessary precondition. Insights into cognitive structures and processes underlying successful human reasoning and planning can provide suggestions for algorithm design. Even more important, insights into restrictions and typical errors and misconceptions of the cognitive systems provide information about those parts of a complex task from which the human should be relieved. For successful human-computer interaction in complex domains it has, furthermore, to be decided which information should be presented when, in what way, to the user. We strongly believe that symbolic approaches of AI and psychological research of higher cognition are at the core of success for the endeavor to create intelligent assistant system for complex domains. While insight into the neurological processes of the brain and into the realization of basic processes of perception, attention and senso-motoric coordination are important for the basic understanding of the principles of human intelligence, these processes have a much too fine granularity for the design and realization of interactive systems which must communicate with the user on knowledge level. If human system users are not to be incapacitated by a system, system decisions must be transparent for the user and the system must be able to provide explanations for the reasons of its proposals and recommendations. Therefore, even when some of the underlying algorithms are based on statistical or neuronal approaches, the top-level of such systems must be symbolical and rule-based. The papers presented at this workshop on complex cognition give an inspiring and promising overview of current work in the field which can provide first building stones for our endeavor to create knowledge level intelligent assistant systems for complex domains. The topics cover modelling basic cognitive processes, interfacing subsymbolic and symbolic representations, dealing with continuous time, Bayesian identification of problem solving strategies, linguistically inspired methods for assessing complex cognitive processes and complex domains such as recognition of sketches, predicting changes in stocks, spatial information processing, and coping with critical situations

Non-Standard Sound Synthesis with Dynamic Models

Full version unavailable due to 3rd party copyright restrictions.This Thesis proposes three main objectives: (i) to provide the concept of a new generalized non-standard synthesis model that would provide the framework for incorporating other non-standard synthesis approaches; (ii) to explore dynamic sound modeling through the application of new non-standard synthesis techniques and procedures; and (iii) to experiment with dynamic sound synthesis for the creation of novel sound objects. In order to achieve these objectives, this Thesis introduces a new paradigm for non-standard synthesis that is based in the algorithmic assemblage of minute wave segments to form sound waveforms. This paradigm is called Extended Waveform Segment Synthesis (EWSS) and incorporates a hierarchy of algorithmic models for the generation of microsound structures. The concepts of EWSS are illustrated with the development and presentation of a novel non-standard synthesis system, the Dynamic Waveform Segment Synthesis (DWSS). DWSS features and combines a variety of algorithmic models for direct synthesis generation: list generation and permutation, tendency masks, trigonometric functions, stochastic functions, chaotic functions and grammars. The core mechanism of DWSS is based in an extended application of Cellular Automata. The potential of the synthetic capabilities of DWSS is explored in a series of Case Studies where a number of sound object were generated revealing (i) the capabilities of the system to generate sound morphologies belonging to other non-standard synthesis approaches and, (ii) the capabilities of the system of generating novel sound objects with dynamic morphologies. The introduction of EWSS and DWSS is preceded by an extensive and critical overview on the concepts of microsound synthesis, algorithmic composition, the two cultures of computer music, the heretical approach in composition, non- standard synthesis and sonic emergence along with the thorough examination of algorithmic models and their application in sound synthesis and electroacoustic composition. This Thesis also proposes (i) a new definition for “algorithmic composition”, (ii) the term “totalistic algorithmic composition”, and (iii) four discrete aspects of non-standard synthesis

Unexpected Aspects of Expectancy in Music: A Spreading Activation Explanation

A well agreed discourse in music perception research is that affective response can be generated by music when a tendency in the music is delayed or inhibited. There is a consensus that this tendency is statistically driven, derived from exposure to culturally situated musical idioms. By presenting a neural-network inspired spreading activation model (SAM) this paper argues that the nature of the tendency is worthy of further investigation. SAM organises the music stream perceived by the listener continuously into segments such that a match with an existing ‘mental representation’ (node) is found, which is then linked to the node for the previously segmented part of the music stream, with the link between these nodes strengthening and consolidating with exposure. The currently activated segment (the music being sounded) will prime the best matching (strongest linked) node available, generating expectancy. Expectancy is defined as the most strongly primed segment, and emerges dynamically through experience with environmental and musical contexts, rather than schematic or prototypical means. Expectancy is the specific exemplar instance that the activated (currently sounding) segment of music and contextual factors prime. This hypothesis of veridical dominance has implications for enduring aspects of music expectancy theory: (1) individual experiences matter in the formation of expectations; (2) expectations are a dynamic process, that change and are updated with experience; (3) context plays a critical role in expectancy; and (4) schema, prototypes and statistical accounts of expectation should be treated as convenient approximations of underlying cognitive processes

Biological roots of musical epistemology: Functional cycles, Umwelt, and enactive listening

Musicologie (OE) Academische lerarenopleiding Letteren.status: publishe

Embodied Resilience in Unaccompanied Latin American Children in a United States Reception Center

The purpose of this study was to explore ways in which a group of unaccompanied children (UC) from El Salvador, Guatemala, Honduras, and Brazil embodied resilience during their stay at a temporary reception center in the United States. The center was located in Illinois and received funding from the Office of Refugee Resettlement (ORR), under the U.S. Department of Health and Human Services. The 12-week clinical case study included a total of 19 male participants aged 12 to 17 years old attending dance/movement therapy sessions, which were scheduled weekly. Group progress notes and individual movement assessment coding sheets were completed and analyzed. A strengths-based lens was utilized to identify and understand resilience-related patterns and processes in participants. Conclusions include identification of participants’ individual and collective embodied resilience and the role of dance/movement therapy in fostering collective embodied resilience through rhythmic group activity. The author identified bound flow and enclosing shaping qualities among participants’ ways of coping with and adjusting to the immigration detention environment. 70 pages

A Cognitive Systems Framework for Creative Problem Solving

This thesis provides a theoretical framework for a wide variety of types of cognitively-inspired creative problem solving. The framework (CreaCogs) is formalized and its various creative processes detailed. The framework is put to the test in a few computational implementations: a solver to the Remote Associates Test - comRAT-C, its adaptation to the visual domain - comRAT-V, and an object replacement and object composition system in a household domain - OROC. The performance and process of these implementations are then (i) compared to human answers and performance in creativity tests or (ii) assessed with the same toolkit that would be used to assess human answers. A set of practical insight problems with objects are given to human participants in a think aloud protocol, which is then encoded and compared to the framework. The experiments and data analysis show that the framework is successful in computationally modeling creative problem solving across a wide variety of tasks

Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009

Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI – to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI – the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In recent years, however, more and more researchers have recognized the necessity – and feasibility – of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence