We present a method to learn visual attributes (eg.“red”,
“metal”, “spotted”) and object classes (eg. “car”,
“dress”, “umbrella”) together. We assume imag...
A connectionist model for robust reasoning, CONSYDERR, is proposed to account for some common reasoning patterns found in commonsense reasoning and to remedy the brittleness probl...
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Cognitive Agents must be able to decide their actions based on their recognized states. In general, learning mechanisms are equipped for such agents in order to realize intellgent ...
Much like relational probabilistic models, the need for relational preference models arises naturally in real-world applications where the set of object classes is fixed, but obj...