17 citations · 48 across the 11 of their papers we have counts for
10 papers · 1 filter
BADGER: Learning to (Learn [Learning Algorithms] through Multi-Agent Communication)
Marek Rosa, Olga Afanasjeva, Simon Andersson +6
In this work, we propose a novel memory-based multi-agent meta-learning architecture and learning procedure that allows for learning of a shared communication policy that enables t…
ToyArchitecture: Unsupervised Learning of Interpretable Models of the World
Jaroslav Vítků, Petr Dluhoš, Joseph Davidson +10
Research in Artificial Intelligence (AI) has focused mostly on two extremes: either on small improvements in narrow AI domains, or on universal theoretical frameworks which are usu…
General AI Challenge - Round One: Gradual Learning
Jan Feyereisl, Matej Nikl, Martin Poliak +2
The General AI Challenge is an initiative to encourage the wider artificial intelligence community to focus on important problems in building intelligent machines with more general…
A Framework for Searching for General Artificial Intelligence
Marek Rosa, Jan Feyereisl, The GoodAI Collective
There is a significant lack of unified approaches to building generally intelligent machines. The majority of current artificial intelligence research operates within a very narrow…
Self-Organising Maps in Computer Security
Jan Feyereisl, Uwe Aickelin
Some argue that biologically inspired algorithms are the future of solving difficult problems in computer science. Others strongly believe that the future lies in the exploration o…
ToLeRating UR-STD
Jan Feyereisl, Uwe Aickelin
A new emerging paradigm of Uncertain Risk of Suspicion, Threat and Danger, observed across the field of information security, is described. Based on this paradigm a novel approach…
The DCA:SOMe Comparison A comparative study between two biologically-inspired algorithms
Julie Greensmith, Jan Feyereisl, Uwe Aickelin
The Dendritic Cell Algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation…
STORM - A Novel Information Fusion and Cluster Interpretation Technique
Jan Feyereisl, Uwe Aickelin
Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for bet…
Detecting Motifs in System Call Sequences
William O. Wilson, Jan Feyereisl, Uwe Aickelin
The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the Motif Tracking Algorithm, a novel immune inspired pat…
Artificial Immune Tissue using Self-Orgamizing Networks
Jan Feyereisl, Uwe Aickelin
As introduced by Bentley et al. (2005), artificial immune systems (AIS) are lacking tissue, which is present in one form or another in all living multi-cellular organisms. Some hav…