By W. Teahan
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Extra resources for Artificial Intelligence - Agents and Environments [math]
7 looks at what virtual environments are. 8 highlights how we can use virtual environments to test out our AI systems. 1 What is an Agent? Agent-oriented systems have developed into one of the most vibrant and important areas of computer science. Historically, one of the primary focus areas in AI has been on building intelligent systems. A standard textbook in AI written by Russell and Norvig (2002) adopts the concept of rational agents as central to their approach to AI. The emphasis is on developing agent systems “that can reasonably be called intelligent” (Russell & Norvig, 2003; page 32).
1 illustrates how objects are abstractions to entities in real life. Three objects are depicted in the diagram – Bill who is an instance of the HumanClass, Tooty who is an instance of the DogClass and Timothy who is an instance of the LambClass. (Objects are also called ‘instances’ of a particular class). 1 Object-oriented design: How objects are abstractions of entities in real life. How do agents differ from objects? Wooldridge (2002; pages 25-27) provides the following answer: Agents have a stronger degree of autonomy than objects.
A discrete environment has a finite number of possible states, whereas the number of states in a continuous environment is infinite. A multiple-agent environment the agent that acts cooperatively or competitively with another agent. If this is not the case, then from the perspective of the agent, the other agents can be viewed as part of the environment that is behaving stochastically. 7 Attributes of environments (based on Wikipedia entry for ‘Intelligent Agents’). The analogy of an environment being like the world we live in is often implicitly used when the term ‘environment’ is used in computer science and AI in particular.