Consciousness, Action Selection, Meaning and Phenomenic Anticipation

Phenomenal states are generally considered the ultimate sources of intrinsic motivation for autonomous biological agents. In this article, we will address the issue of the necessity of exploiting these states for the design and implementation of robust goal-directed artificial systems. We will provide an analysis of consciousness in terms of a precise definition of how an agent "understands" the informational flows entering the agent and its very own action possibilities. This abstract model of consciousness and understanding will be based in the analysis and evaluation of phenomenal states along potential future trajectories in the state space of the agents. This implies that a potential strategy to follow in order to build autonomous but still customer-useful systems is to embed them with the particular, ad hoc phenomenality that captures the system-external requirements that define the system usefulness from a customer-based, requirements-strict engineering viewpoint

Toward Self-Referential Autonomous Learning of Object and Situation Models

Most current approaches to scene understanding lack the capability to adapt object and situation models to behavioral needs not anticipated by the human system designer. Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize behavior. This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome. Besides proposing architectural concepts, we also describe a first implementation of our system within a simulated traffic scenario to demonstrate the feasibility of our approach

Antiviral Silencing and Suppression of Gene Silencing in Plants

RNA silencing is an evolutionary conserved sequence-specific gene inactivation mechanism that contributes to the control of development, maintains heterochromatin, acts in stress responses, DNA repair and defends against invading nucleic acids like transposons and viruses. In plants RNA silencing functions as one of the main immune systems. RNA silencing process involves the small RNAs and trans factor components like Dicers, Argonautes and RNA-dependent RNA poly- merases. To deal with host antiviral silencing responses viruses evolved mecha- nisms to avoid or counteract this, most notably through expression of viral suppressors of RNA silencing. Due to the overlap between endogenous and antiviral silencing pathways while blocking antiviral pathways viruses also impact endogenous silencing processes. Here we provide an overview of antiviral silencing pathway, host factors implicated in it and the crosstalk between antiviral and endogenous branches of silencing. We summarize the current status of knowledge about the viral counter-defense strategies acting at various steps during virus infection in plants with the focus on representative, well studied silencing suppres- sor proteins. Finally we discuss future challenges of the antiviral silencing and counter-defense research field