Authors:
Mirgita Frasheri
;
Baran Cürüklü
and
Mikael Ekström
Affiliation:
Mälardalen University, Sweden
Keyword(s):
Adaptive Autonomy, Multi-agent Systems, Collaborative Agents.
Related
Ontology
Subjects/Areas/Topics:
Agent Models and Architectures
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Autonomous Systems
;
Bioinformatics
;
Biomedical Engineering
;
Cooperation and Coordination
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
Adaptive autonomy (AA) is a behavior that allows agents to change their autonomy levels by reasoning on their
circumstances. Previous work has modeled AA through the willingness to interact, composed of willingness
to ask and give assistance. The aim of this paper is to investigate, through computer simulations, the behavior
of agents given the proposed computational model with respect to different initial configurations, and level of
dependencies between agents. Dependency refers to the need for help that one agent has. Such need can be
fulfilled by deciding to depend on other agents. Results show that, firstly, agents whose willingness to interact
changes during run-time perform better compared to those with static willingness parameters, i.e. willingness
with fixed values. Secondly, two strategies for updating the willingness are compared, (i) the same fixed value
is updated on each interaction, (ii) update is done on the previous calculated value. The maximum number of
completed
tasks which need assistance is achieved for (i), given specific initial configurations.
(More)