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...
Theoretical and empirical work on the geometry of environmental knowledge is discussed. Certain patterns of distanc.e and directional estimates collected from humans have been inte...
: This paper examines the argument for dataflow architectures in "Two Fundamental Issues in Multiprocessing[5]." We observe two key problems. First, the justification of ...
Although concept maps have been found to be effective in science education research, these are critiqued for being informal due to informal usage of relation and attribute names t...
We study how the choice of packet scheduling algorithms influences end-to-end performance on long network paths. Taking a network calculus approach, we consider both deterministi...