504 research outputs found

    On Repairing Reasoning Reversals via Representational Refinements

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    Representation is a fluent. A mismatch between the real world and an agent’s representation of it can be signalled by unexpected failures (or successes) of the agent’s reasoning. The ‘real world ’ may include the ontologies of other agents. Such mismatches can be repaired by refining or abstracting an agent’s ontology. These refinements or abstractions may not be limited to changes of belief, but may also change the signature of the agent’s ontology. We describe the implementation and successful evaluation of these ideas in the ORS system. ORS diagnoses failures in plan execution and then repairs the faulty ontologies. Our automated approach to dynamic ontology repair has been designed specifically to address real issues in multi-agent systems, for instance, as envisaged in the Semantic Web

    An Automatic Translator from KIF to PDDL

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    In this paper, we present a translation process that we have developed to convert KIF ontologies into PDDL. This allows us to define KIF-based agents that can plan efficiently. We discuss the difficulties inherent in such a translation process, and the steps we have taken to overcome them. This process is translates from only a subset of KIF to a corresponding subset of PDDL

    Strigolactone signaling through the eye of the mass spectrometer

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    Quantitative tandem affinity purification, an effective tool to investigate protein complex composition in plant hormone signaling : strigolactones in the spotlight

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    Phytohormones tightly regulate plant growth by integrating changing environmental and developmental cues. Although the key players have been identified in many plant hormonal pathways, the molecular mechanisms and mode of action of perception and signaling remain incompletely resolved. Characterization of protein partners of known signaling components provides insight into the formed protein complexes, but, unless quantification is involved, does not deliver much, if any, information about the dynamics of the induced or disrupted protein complexes. Therefore, in proteomics research, the discovery of what actually triggers, regulates or interrupts the composition of protein complexes is gaining importance. Here, tandem affinity purification coupled to mass spectrometry (TAP-MS) is combined with label-free quantification (LFQ) to a highly valuable tool to detect physiologically relevant, dynamic protein-protein interactions in Arabidopsis thaliana cell cultures. To demonstrate its potential, we focus on the signaling pathway of one of the most recently discovered phytohormones, strigolactones
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