Third edition of Artificial Intelligence: foundations of computational agents, Cambridge University Press, 2023 is now available (including the full text).
1.8 Review
The following are the main points you should have learned from this chapter:
- Artificial intelligence is the study of computational agents that act intelligently.
- An agent acts in an environment and only has access to its prior knowledge, its history of observations, and its goals and preferences.
- An intelligent agent is a physical symbol system that manipulates symbols to determine what to do.
- A designer of an intelligent agent should be concerned about modularity, how to describe the world, how far ahead to plan, uncertainty in both perception and the effects of actions, the structure of goals or preferences, other agents, how to learn from experience, and the fact that all real agents have limited computational resources.
- To solve a problem by computer, the computer must have an effective representation with which to reason.
- To know when you have solved a problem, an agent must have a definition of what constitutes an adequate solution, such as whether it has to be optimal, approximately optimal, or almost always optimal, or whether a satisficing solution is adequate.
- In choosing a representation, you should find a representation that is as close as possible to the problem, so that it is easy to determine what it is representing and so it can be checked for correctness and be able to be maintained. Often, users want an explanation of why they should believe the answer.
