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We use Python because Python programs can be close to pseudo-code. It is designed for humans to read. Python is reasonably efficient. Efficiency is usually not a problem for small examples. If your Python code is not efficient enough, a general procedure to improve it is to find out what is taking most the time, and implement just that part more efficiently in some lower-level language. Most of these lower level languages interoperate with Python nicely. This will result in much less programming and more efficient code (because you will have more time to optimize) than writing everything in a low-level language. You will not have to do that for the code here if you are using it for course projects.
Python for Artificial Intelligence.
Agent Architectures and Hierarchical Control.
Searching for Solutions.
Reasoning with Constraints.
Propositions and Inference.
Deterministic Planning.
Supervised Machine Learning.
Neural Networks and Deep Learning.
Reasoning with Uncertainty.
Learning with Uncertainty.
Causality.
Planning with Uncertainty.
Reinforcement Learning.
Multiagent Systems.
Individuals and Relations.
Knowledge Graphs and Ontologies.
Relational Learning.
Version History.
Bibliography.
Index