Architectures For Activity Recognition And Context-Aware Computing

Abstract

The Special issue of AI Magazine brings together extended versions of selected papers from the 2013 Plan, Activity, and Intent Recognition workshops and the Activity Context-Aware Systems workshops to highlight the state of the art in the technologies that enable these new methods of interacting with virtual and cyber physical systems. Oriel Uzan, Reuth Dekel, Or Seri, and Ya'akov Gal's article, Plan Recognition for Exploratory Learning Environments Using Interleaved Temporal Search, presents novel algorithms for inferring users' activities in a class of flexible and open-ended educational software called exploratory learning environments (ELEs) that support interaction styles including exogenous actions and trial and error, providing a rich educational environment for students but challenging teachers to keep track of students' progress and to assess their performance. Christopher W. Geib and Christopher E. Swetenham's article, Parallelizing Plan Recognition, exploits the opportunity provided by modern multicore computing devices to parallelize plan recognition algorithms to decrease run time. Mik Kersten and Gail C. Murphy show in their article, Reducing Friction for Knowledge Workers with Task Context, how this friction can be reduced, and productivity improved, by capturing and modeling the context of a knowledge worker's task based on how the knowledge worker interacts with an information space. Computational management of activities that reflect human intention through activity-based computing (ABC) is described by Jakob E. Bardram, Steven Jeuris, and Steven Houben in their article, Activity-Based Computing: Computational Management of Activities Reflecting Human Intention. In their article, A General Context-Aware Framework for Improved Human System Interactions, Stacy Lovell Pfautz, Gabriel Ganberg, Adam Fouse, and Nathan Schurr describe a general framework for building context-aware interactive intelligent systems.

Publication Date

6-1-2015

Publication Title

AI Magazine

Volume

36

Issue

2

Number of Pages

3-9

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1609/aimag.v36i2.2578

Socpus ID

85027275220 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85027275220

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