This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

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AI is the part of computer science concerned with designing intelligent computer systems, that is, computer systems that exhibit the characteristics we associate with intelligence in human behaviour – understanding language, learning, reasoning and solving problems.A theme we will develop in this course is that most AI systems :

• Search,
• Knowledge Representation,
• applications of the above.
• Knowledge representation deals with finding a means of encoding knowledge so that a machine can use it.
• e.g Expert systems have to work with a knowledge base as do many other reasoning tasks.
• We will look at knowledge representation early on in this course.

• Tasks such a planning, reasoning, learning, understanding basically involve some searching and perhaps updating of a knowledge base.
• Tasks such as vision, natural language understanding, speech recognition and robot planning involve searching knowledge also. We will look at some of these tasks in the remainder of the course.   Book Link: http://www.cs.cf.ac.uk/Dave/AI2/AI_notes.html

A I is the study of how to make computers do things which at the moment people do better. This is ephemeral as it refers to the current state of computer science and it excludes a major area ; problems that cannot be solved well either by computers or by people at the moment.A I is about generating representations and procedures that automatically or autonomously solve problems heretofore solved by humans.A I is the part of computer science concerned with designing intelligent computer systems, that is, computer systems that exhibit the characteristics we associate with intelligence in human behaviour — understanding language, learning, reasoning and solving problems.

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This book is for you if you’re curious about Common Lisp, regardless of whether you’re already convinced you want to use it or if you just want to know what all the fuss is about.
If you’ve learned some Lisp already but have had trouble making the leap from academic exercises to real programs, this book should get you on your way. On the other hand, you don’t have to be already convinced that you want to use Lisp to get something out of this book.
If you’re a hard-nosed pragmatist who wants to know what advantages Common Lisp has over languages such as Perl, Python, Java, C, or C#, this book should give you some ideas.
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