Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
Real organisms live in a world full of uncertain situations and have evolved cognitive mechanisms to cope with problems based on actions and perceptions which are not always reliab...
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Our previous research illustrated the design of fuzzy logic based online risk assessment for Distributed Intrusion Prediction and Prevention Systems (DIPPS) [3]. Based on the DIPP...
— In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera. O...