Computational models of motivation are tools that artificial agents can use to autonomously identify, prioritize, and select the goals they will pursue. Previous research has focu...
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
Argumentation is a promising approach used by autonomous agents for reasoning about inconsistent/incomplete/uncertain knowledge, based on the construction and the comparison of ar...
The distributed constraint satisfaction problem (CSP) is a general formalisation used to represent problems in distributed multiagent systems. To deal with realistic problems, mult...
—Application mobility is an efficient way to mask uneven conditioning and reduce users’ distractions in pervasive environments. However, since mobility brings more dynamism and...