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Simulations of embodied evolving semiosis: Emergent semantics in artificial environments

Simulations of embodied evolving semiosis: Emergent semantics in artificial environments,LUIS MATEUS ROCHA,CLIFF JOSLYN

Simulations of embodied evolving semiosis: Emergent semantics in artificial environments   (Citations: 3)
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As we enter this amazing new world of artificial and virtual systems and environments in the context of human communities, we are interested in the development of systems and environments which have the capacity to grow and evolve their own meanings in the context of this community of interaction. In this paper the authors analyze the necessary conditions to achieve systems and environments with these properties: (1) a coupled interaction between a system and its environment; (2) an environment with sufficient initial richness and structure to allow for; (3) embodied emergent classification of that environment system coupling; and (4) which is subject to pragmatic selection.
Published in 1998.
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    • ...The state-determined transition rules are interpreted as the laws of some physical system [34, 55]: The state of each component depends on the states of its neighbor (or related) components at the previous time instant...
    • ...Indeed, the emergent behavior of agents that are dynamically coherent with their environments (embodied agents) is as much a result of the production rules of the agent as of the laws of the environment [5, 8, 55]...

    Luis Mateus Rochaet al. Material Representations: From the Genetic Code to the Evolution of Ce...

    • ...It replaced the traditional high-level control by scheme of functional modularization of behavior generating modules (Rocha and Joslyn, 1998...

    Yasser Hassanet al. Emergent rough set data analysis

    • ...Hence, a problem addressed in this paper is to establish a certain background for constructing emergent system structure [7, 14], which might be able to perform basic rough set operations, in particular, those that reduce the redundancy of knowledge, if any...
    • ...Traditionally, AI relied strongly on models of representation and direct perception of the world [14]...
    • ...Instead of high–level computation of behavior, the bottom–up (emergent) self–organization of simpler components produces a variety of behaviors depending on the interaction of the agent with its environment [15, 5]. The structure coupling of the agent and its environment is the source of the behavior, and not just the agent control system alone [14]...
    • ...Let us consider an idealized means of prediction in that complex system, requiring an amount of computation ωopt(n) based on perfect understanding [14]...
    • ...Global properties that prevail for a system as a whole, but cannot or do not exist within individual components of that system, are called emergent properties [14]...

    Yasser Hassanet al. Emergent Rough Set Data Analysis

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