The paper argues that the agent paradigm in AI is conceptually ambiguous and anthropocentric, and that next-generation intelligence may be better pursued through system-level, world-model, and material-computing frameworks.
A Systematic Approach to Artificial Agents
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abstract
Agents and agent systems are becoming more and more important in the development of a variety of fields such as ubiquitous computing, ambient intelligence, autonomous computing, intelligent systems and intelligent robotics. The need for improvement of our basic knowledge on agents is very essential. We take a systematic approach and present extended classification of artificial agents which can be useful for understanding of what artificial agents are and what they can be in the future. The aim of this classification is to give us insights in what kind of agents can be created and what type of problems demand a specific kind of agents for their solution.
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Is the `Agent' Paradigm a Limiting Framework for Next-Generation Intelligent Systems?
The paper argues that the agent paradigm in AI is conceptually ambiguous and anthropocentric, and that next-generation intelligence may be better pursued through system-level, world-model, and material-computing frameworks.