TY - CHAP
T1 - Adjustable autonomy challenges in personal assistant agents
T2 - a position paper
AU - Maheswaran, Rajiv T.
AU - Tambe, Milind
AU - Varakantham, Pradeep
AU - Myers, Karen
N1 - ID number: ISIP:000223492900015
PY - 2004
Y1 - 2004
N2 - The successful integration and acceptance of many multiagent systems into daily lives crucially depends on the ability to develop effective policies for adjustable autonomy. Adjustable autonomy encompasses the strategies by which an agent selects the appropriate entity (itself, a human user, or another agent) to make a decision at key moments when an action is required. We present two formulations that address this issue: user-based and agent-based autonomy. Furthermore, we discuss the current and future implications on systems composed of personal assistant agents, where autonomy issues are of vital interest.
AB - The successful integration and acceptance of many multiagent systems into daily lives crucially depends on the ability to develop effective policies for adjustable autonomy. Adjustable autonomy encompasses the strategies by which an agent selects the appropriate entity (itself, a human user, or another agent) to make a decision at key moments when an action is required. We present two formulations that address this issue: user-based and agent-based autonomy. Furthermore, we discuss the current and future implications on systems composed of personal assistant agents, where autonomy issues are of vital interest.
UR - https://www.scopus.com/pages/publications/35048831418
M3 - Book chapter
SN - 9783540224778
T3 - Lecture Notes in Computer Science
SP - 187
EP - 194
BT - Agents and Computational Autonomy
A2 - Nickles, M
A2 - Rovatsos, M
A2 - Weiss, G
PB - Springer
CY - Berlin, Germany
ER -