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The Virtue of Reward: Performance, Reinforcement and Discovery in Case-Based Reasoning

  • Derek Bridge
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3620)

Abstract

Agents commonly reason and act over extended periods of time. In some environments, for an agent to solve even a single problem requires many decisions and actions. Consider a robot or animat situated in a real or virtual world, acting to achieve some distant goal; or an agent that controls a sequential process such as a factory production line; or a conversational diagnostic system or recommender system. Equally, over its life time, a long-lived agent will make many decisions and take many actions, even if each problem-solving episode requires just one decision and one action. In spam detection, for example, each incoming email requires a single classification decision before it moves to its designated folder; but continuous operation requires numerous decisions and actions.

Keywords

Recommender System Virtual World Concept Drift Single Problem Reinforcement Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Derek Bridge
    • 1
  1. 1.Department of Computer ScienceUniversity CollegeCorkIreland

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