Analysis Back

Mapping Weak Signals

Inspired by: FP7 » Humanoids that learn socio-communicative skills by observation

version: 1 / created: 2010-01-03
id: #676 / version id: #676
mode: VIEW

Originally submitted by: Martin Fatun
List of all contributors by versions (mouse over)
Last changed by: Martin Fatun
WI-WE status:

submitted

unpublished

archived

Source of inspiration

European Commission Framework Programme for RTD (FP7)

Theme/activity of inspiration

Theme 3 - ICT - Information & communication technologies

Sub-theme/area of inspiration

Cognitive systems, interaction, robotics

Optional reference/s to FP7 project/s

Use the following format: Project Acronym (Project Reference No.). Use commas if more than one project is associated to this Wild Card, for example: ALFA-BIRD (213266), SAFAR (213374), LAPCAT-II (211485)

HUMANOBS (231453)

Signal's headline

(max. 9 words)

Humanoids that learn socio-communicative skills by observation

Signal's description

(approx. 150 words)

Please describe the Weak Signal (approx. 150 words)

Human communicative skills rely on a complex mixture of social and spatio-temporal perception-action processes. Autonomous virtual agents that interact with people could benefit greatly from socio-communicative skills; endowing them with such skills, however, could mean decades of person-years in manual programming. Enabling the agents to learn these skills is an alternative solution the learning mechanisms for this, however, are also well beyond the state of the art. The goal of the HUMANOBS project is to develop new cognitive architectural principles to allow intelligent agents to learn socio-communicative skills by observing and imitating people in dynamic social situations on the job.

Keywords

ICT, robotics, robot, humanoid, socio-comunicative skills, intelligent agents

Signal's first apperance

2005-now

Progress: 31.25% WWI-WE Version: 1
0	mandatory questions pending
19	questions total
5	questions answered
5	questions completed
14	questions pending