We propose a computational model that facilitates agents in a MAS to collaboratively evolve their norms to reach the best norm conventions. Our approach borrows from the social con...
Nowadays, large distributed databases are commonplace. Client applications increasingly rely on accessing objects from multiple remote hosts. The Internet itself is a huge network ...
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, ...
We analyse a suite of Boolean networks which have been evolved to exhibit limit cycle-type dynamics in terms of the distribution of small network motifs and feedback loops. We find...
This paper presents a novel system that employs an adaptive neural network for the no-reference assessment of perceived quality of JPEG/JPEG2000 coded images. The adaptive neural ...