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Scenario² (page 1 of 3)

Dennis Del Favero, Jeffrey Shaw, Steve Benford, Johannes Goebel
2005 - 2010
Machine Agent Interactive Narrative

Scenario² investigates the asymmetry in narrative reasoning between machine agents and human participants in interactive cinema. It argues that when machine agents are provided with a modest ability to sense and interpret symbolically the actions of real participants sharing a mixed reality environment, their interactive responses will co-evolve autonomously with those of human participants. In an experimental encounter with human participants, adapted from Samuel Beckett, the study tests the narrative autonomy of machine agents as the capacity to deliberate in reference to sensory tracking, represented through a symbolic language, in consultation with a body of scripted beliefs.

Scenario² in AVIE

Objectives
Explain co-evolutionary narrative as the interaction between human participants and an autonomous machine agent. Narrative autonomy of machine agents is defined as the capacity to act in reference to sensory tracking, represented through a symbolic language, in consultation with a body of belief/desires. The satisfaction of narrative autonomy by machine agents is twofold. Firstly, although an artifice, an agent is obliged to act on its own deliberation in response to meanings they ascribe to an emergent situation. Secondly an agent’s intentions must be recoverable through symbolic reasoning originating within their own scripted beliefs.
Test outcomes of co-evolutionary interaction between participant and machine agent in a cinematic experiment, which derive their scripting from Samuel Beckett, entitled Scenario², and are conducted within a uniquely designed advanced visualisation and interaction environment. Scenario² involves the apprehension, interpretation and response by multiple machine agents to clusters of more that one human participant, thus focusing upon group interaction.
Evaluate the significance of co-evolutionary narrative as a condition of: differentiated clarity in sensing and tracking; autonomy recoverable in the deliberation of machine agents; quality of aesthetic conviction in the co-evolutionary responses of machine and human participants.


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