A standard model of how brains produce natural cognition would provide a framework for organizing cognitive neuroscience research. A recent effort (Laird et al., in press) to build on consensus views of cognitive operations and produce a standard model of natural cognition started with common aspects of well-established cognitive architectures ACT-R, Sigma, and SOAR. The model captures scientific consensus on “how” the brain works, but it does not offer a coherent story for “why” the component modules (i.e., working memory, long-term memory, visual and motor areas) exist and interact in the ways described. This manuscript starts with background information on a well-cited theory of action selection, and extends that theory to a fuller explanation of decision-making, action and perception that includes a framework for the elements of cognition.

Human-level cognition (most uniquely characterized by our abilities to use language) should be seen as a superset of functional and behavioral capabilities shared by lower life-forms including animals and insects, and this perspective ought to principally guide our strategies for developing integrated cognitive architectures. Just as the study of biological model organisms has led to tremendous advances in our scientific knowledge of genetics and cellular function, the study of embodied cognition in simple agent-environment simulations can yield similar advances in Cognitive Science, Artificial Intelligence, and Robotics. By working first on the foundations of intelligent interaction with one’s environment, and by focusing on core functions such as predictive and inductive learning, probabilistic goal-directed behavior compilation, and empathetic reasoning, we can better establish the grounding that the physical symbol system hypothesis assumes (Newell and Simon 1976), yet often without explicit demonstration of a mechanism to derive symbolic relations and semantics from raw sensory data. Logic and language are seen to emerge from our willingness to make discrete simplifying assumptions in a continuous and probabilistic world of experience, and developing a Standard Model of the Mind can help build much-needed bridges between historically non-aligned research communities.

The legal relationship between government and citizens is mediated by documents. This paper identifies four classes of cognitive assistants that could improve the experience of citizens and government officials in using and understanding government documents: self-filling forms; error-detecting forms; proactive information search; and deductive document synthesis. Each of these classes of cognitive assistants has the potential to significantly improve access to justice and delivery of information, services, and other benefits to citizens by improving the ability of citizens to understand and correctly fill out forms and to comprehend informational documents.

Two features of microtext that challenge language processing tools are addressed in the context of linking messages in the emergency response domain. First, the effect of very short texts on several classifiers is estimated by comparing the results when classifiers are applied to the full text of news reports vs. only the headlines. These experiments demonstrate a decrease of 5 - 20% in accuracy. A second challenging feature of microtexts is their accumulation in real time, which can be massive for sources such as Twitter. A dynamic hierarchical clustering algorithm that clusters messages as they accumulate is described, and a preliminary experiment in clustering tweets is demonstrated.

Nearly all humor derives from some element of surprise, discrepancy, unexpectedness, pattern-breaking, or anomalous inference. This speculative paper will briefly discuss aspects of linguistic humor, from simple wordplay including shm-reduplication, punning, simple language games, simple humorous linguistic and textual genres (limericks, Pig Latin, “Name Game”), to more complex genres that go beyond humor into linguistic and textual artistic innovation such as modernism (Joyce’s Ulysses, Finnegan’s Wake), post-modernism (Theater of the Absurd, Beckett, John Barth’s Giles Goat Boy, Chimera), OuLiPo (Ouvroir de Litterature Potentielle, “workshop for potential literature”) (constraint-based postmodernism), and science fiction (world creation). In many cases, both humor and linguistic and textual innovation can be considered to have notions of friction or pressure within a constrained communicative channel, and more generally as breaking a common linguistic pattern based on implicit or explicit meta-linguistic constraints. My speculative approach includes developing a linguistic spectrum (from phono-morphological to discourse components and beyond) to describe the range of techniques used for humor, but also a very early foray into a theoretical account of humor and creativity that focuses on creating an object-level design space (structure and model) that is guided by meta-linguistic constraints.

Since the early days of quantum theory, the concept of wave function collapse has been looked upon as mathematically unquantifiable, observer-dependent, non-local, or simply inelegant. Consequently, modern interpretations of quantum theory often try to avoid or make irrelevant the need for wave collapse. This is ironic, since experimental quantum physics requires some variant of wave collapse wherever quantum phenomena interact with the classical universe of the observer. This paper proposes a pragmatic view in which wave function collapses are treated as real phenomena that occur in pairs. Paired collapses occur when two wave packets exchange real (vs. virtual) momentum-carrying force particles such as photons. To minimize reversibility, such pairs must be separated by a relativistically time-like interval. The resulting model resembles a network of future-predictive simulations (wave packets) linked together by occasional exchanges of data (force particles). Each data exchange “updates” the wave packets by eliminating the need for them to “consider” some range of possible futures. The rest of the paper explores the information processing implications of this idea of networked wave packets. It is postulated that similar networks of simulations in classical computers could provide faster, more efficient ways to process sensor data.

The Association for the Advancement of Artificial Intelligence was pleased to present the 2008 Fall Symposium Series, held Friday through Sunday, November 7-9, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia were (1) Adaptive Agents in Cultural Contexts, (2) AI in Eldercare: New Solutions to Old Problems, (3) Automated Scientific Discovery, (4) Biologically Inspired Cognitive Architectures, (5) Education Informatics: Steps toward the International Internet Classroom, (6) Multimedia Information Extraction, and (7) Naturally Inspired AI.

These underpinnings in genetics and fields are vast, variegated, informed by memetics, studying phenomena such disparate theoretical and technical disciplines, as coalition formation in an artificial and interrelated. Other applications provided an updated perspective ethical concerns related to the use of included case-based retrieval of to a previous symposium held in fall eldercare technology to ensure that narratives culturally relevant to a 2005 on the same topic. Some models focused One major theme of the symposium The symposium ended with a more directly on adaptation, from machine-learning was to investigate the use of sensor brainstorming session on possible solutions and game-theoretic networks in the home environment to for two real-life scenarios for perspectives, but discussions suggested provide safety, to monitor activities of ailing elders and their caregivers. The ways in which those adaptations daily living, to assess physical and cognitive exercise was helpful in grounding the might vary from one cultural context function, and to identify participants in the lives of older adults to another. Work was also should address real needs.