<span title="">1995</span> <i title="WORLD SCIENTIFIC"> Problem Solving in a Dynamic Environment </i> &nbsp;
This dissertation studies how different learning architectures perform in a dynamic environment: an arena containing a bouncing ball, which the agent must catch. In particular, it adds functionality to the agent in a way as to imitate a perceived hierarchy of cognitive faculties possessed by sentient minds. A key role is played by the ability to generalise from learning experiences, and this study attempts to combine reinforcement learning with neural networks to this end. This environment
more &raquo; ... strates the benefits to a table-based learner of short-term memory, a generalising state representation and planning with a Dyna architecture. In contrast, the development of a working neural net-based architecture encountered significant problems. i
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