Perceptual Anchoring with Indefinite Descriptions

Anchoring is the problem of how to connect, inside an artificial system, the symbol-level and signal- level representations of the same physical object. In most previous work on anchoring, symbol-level representations were meant to denote one specific object, like 'the red pen p22'. These are also called definite descriptions. In this paper, we study an- choring in the case of indefinite descriptions, like 'a red pen '. A key point of our study is that an- choring with an indefinite description involves, in general, the selection of one object among several perceived objects that satisfy that description. We analyze several strategies to perform object selec- tion, and compare them with the problem of action selection in autonomous embedded agents.

[1]  Hector J. Levesque,et al.  Intention is Choice with Commitment , 1990, Artif. Intell..

[2]  Alessandro Saffiotti,et al.  Robust color segmentation for the RoboCup domain , 2002, Object recognition supported by user interaction for service robots.

[3]  Michael P. Georgeff,et al.  Commitment and Effectiveness of Situated Agents , 1991, IJCAI.

[4]  Michael Wooldridge,et al.  Principles of intention reconsideration , 2001, AGENTS '01.

[5]  J. Hintikka On denoting what? , 2005, Synthese.

[6]  Alessandro Saaotti Pick-Up What ? , 1994 .

[7]  Alessandro Saffiotti,et al.  Anchoring Symbols to Sensor Data: Preliminary Report , 2000, AAAI/IAAI.

[8]  Michael Wooldridge,et al.  Intention Reconsideration Reconsidered , 1998, ATAL.