This chapter presents a generic internal reward system that drives an agent to increase the complexity of its behavior. This reward system does not reinforce a predefined task. It...
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...
Information contained in the video sequences is crucial for an autonomous robot or a computer to learn and respond to its surrounding environment. In the past, robot vision is mai...
Qiong Liu, Yong Rui, Thomas S. Huang, Stephen E. L...
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...