TitleCase-based goal-driven coordination of multiple learning agents
Publication TypeConference Paper
Year of Publication2013
AuthorsJaidee, U, Muñoz-Avila, H, Aha, DW
Conference NameInternational Conference on Case-Based Reasoning
PublisherSpringer
Conference LocationSaratoga Springs, NY
Keywordscase-based reasoning, Goal reasoning, goal-driven autonomy, multiple agents
Abstract

Although several recent studies have been published on goal
reasoning (i.e., the study of agents that can self-select their goals), none have
focused on the task of learning and acting on large state and action spaces. We
introduce GDA-C, a case-based goal reasoning algorithm that divides the state
and action space among cooperating learning agents. Cooperation between
agents emerges because (1) they share a common reward function and (2)
GDA-C formulates the goal that each agent needs to achieve. We claim that its
case-based approach for goal formulation is critical to the agents’ performance.
To test this claim we conducted an empirical study using the Wargus RTS
environment, where we found that GDA-C outperforms its non-GDA ablation.

Refereed DesignationRefereed
Full Text
pdf: 
http://www.nrl.navy.mil/itd/aic/sites/www.nrl.navy.mil.itd.aic/files/pdfs/%28Jaidee%20et%20al.%2C%20ICCBR-13%20proof%29%20Case-Based%20Goal-Driven%20Coordination%20of%20Multiple%20Learning%20Agents.pdf
NRL Publication Release Number: 
13-1231-0817
pub_tags: 
Goal reasoning
goal-driven autonomy
case-based reasoning
multiple agents
key_pub_tags: