'Autonomy', with 'interaction' the central issue of the new Agent-based AI paradigm, has to be recollected to the internal and external powers and resources of the Agent. Internal. resources are specified by the Agent architecture (and by skills, knowledge, cognitive capabilities, etc.); external resources are provided (or limited) by accessibility, competition, pro-social relations, and norms. 'Autonomy' is a relational and situated notion: the Agent as for a given needed resource and for a goal to be achieved- is autonomous from the environment or from other Agents. Otherwise it is 'dependent' on them. We present this theory of Autonomy (independence, goal autonomy, norm autonomy, autonomy in delegation, discretion, control autonomy, etc.) and we examine how acting within a group or organization reduces and limits the Agent autonomy, but also how this may provide powers and resources and even increase the Autonomy of the Agent.
|Title of host publication||Agents and Computational Autonomy: Potential, Risks, and Solutions|
|Editors||M Nickles, M Rovatsos, G Weiss|
|Number of pages||15|
|Publication status||Published - 2004|
|Name||Lecture Notes in Computer Science|