Perception Based Processing of NL

Extended Abstract 1. It is common practice in theoretical linguistics, formal semantics and cognitive mod-eling to identify real world entities with the (symbolic) structures that represent them. Some of the problems in logics and linguistics that these models encounter, are due to the (crisp) declarative formats of (symbolic, compositional, propositional) representations employed, and the (rule-based, modular, deterministic) procedures chosen in processing language entities (elements, structures, relations, functions, and processes) whose meanings are specified model dependent via truth conditions. In order to understand how natural languages (NL) serve the purposes they do, it has to be investigated what makes a sign stand for (or symbolize) something else. In doing so, procedural and fuzzy approaches to modeling NL understanding have devised some means to come to grips with the dynamics of cognition as a multi-layered process of structure identification [7] that allows to cope with the variability and vagueness, adaptivity and learning, emergence and plasticity of knowledge and understanding [8]. Fuzzy modeling techniques allow for (numerical , sub-symbolic, distributed, non-propositional) formats whose (parallel, pattern-based, quantitative) computation result in (the emergence of) meanings which are the outcome rather than the presuppositions of processing, and whose modeling is a form of realization rather than simulation[3]. 2. Semiotic Cognitive Information Processing (SCIP) models [5, 6] are inspired by information systems theory and concentrate on (natural or artificial) system-environment situations whose knowledge-based processing of information makes them cognitive, and whose sign and symbol generation, manipulation, and understanding capabilities render them semiotic. SCIP systems' ability comprises their performance in knowledge-based information processing and representing its results, organizing these representations by activating others from prior processing, planning acts by selecting from such organized and represented dispositions, and modifying them according to changing conditions, results , and states of evolving system-environment adaptedness. Based on NL structures, SCIP performance is a form of complex, multi-resolutional information processing tied to (and even be identified with) language understanding. Whenever such cognitive processes are modeled as being based upon structures whose representational status is not a pre-supposition to but a result from an algorithmic processing, then these algorithms – being