<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nehaniv, Chrystopher L</style></author><author><style face="normal" font="default" size="100%">Daniel Polani</style></author><author><style face="normal" font="default" size="100%">Kerstin Dautenhahn</style></author><author><style face="normal" font="default" size="100%">René te Boekhorst</style></author><author><style face="normal" font="default" size="100%">Lola Cañamero</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Russell Standish</style></author><author><style face="normal" font="default" size="100%">Mark A Bedau</style></author><author><style face="normal" font="default" size="100%">Hussein A Abbass</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Meaningful Information, Sensor Evolution, and the Temporal Horizon of Embodied Organisms</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life VIII: Proceedings of the Eighth International Conference on Artificial Life</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Sydney, Australia</style></pub-location><pages><style face="normal" font="default" size="100%">345–349</style></pages><isbn><style face="normal" font="default" size="100%">9780262692816</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We survey and outline how an agent-centered, information-theoretic approach to meaningful information extending classical Shannon information theory by means of utility measures relevant for the goals of particular agents can be applied to sensor evolution for real and constructed organisms. Furthermore, we discuss the relationship of this approach to the programme of freeing artificial life and robotic systems from reactivity, by describing useful types of information with broader temporal horizon, for signaling, communication, affective grounding, two-process learning, individual learning, imitation and social learning, and episodic experiential information (memories, narrative, and culturally transmitted information).</style></abstract></record></records></xml>