Prolog Programming for Artificial Intelligence
	3rd Edition
	Ivan Bratko
	ISBN-13: 978-0-20140-375-6
	ISBN-10: 0-20140-375-7
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	readme.txt
	Chapter 01
	Figure 1.8	The family program
	Chapter 02
	Figure 2.14	A program for the monkey and banana problem
	Figure 2.16	Four versions of the predecessor program
	Chapter 04
	Figure 4.5	A flight route planner and an example flight timetable
	Figure 4.7	Program 1 for the eight queens problem
	Figure 4.9	Program 2 for the eight queens problem
	Figure 4.11	Program 3 for the eight queens problem
	Chapter 07
	Figure 7.2	A program for cryptoarithmetic puzzles
	Figure 7.3	A procedure for substituting a subterm of a term by another subterm
	Figure 7.4	An implementation of the findall relation
	Chapter 09
	Figure 9.2	Quicksort
	Figure 9.3	A more efficient implementation of quicksort using difference-pair representation for lists
	Figure 9.7	Finding an item X in a binary dictionary
	Figure 9.10	Inserting an item as a leaf into the binary dictionary
	Figure 9.13	Deleting from the binary dictionary
	Figure 9.15	Insertion into the binary dictionary at any level of the tree
	Figure 9.17	Displaying a binary tree
	Figure 9.20	Finding an acyclic path, Path, from A to Z in Graph
	Figure 9.21	Path-finding in a graph: Path is an acyclic path with cost Cost from A to Z in Graph
	Figure 9.22	Finding a spanning tree of a graph: an 'algorithmic' program
	Figure 9.23	Finding a spanning tree of a graph: a 'declarative' program
	Chapter 10
	Figure 10.6	Inserting and deleting in the 2-3 dictionary
	Figure 10.7	A program to display a 2-3 dictionary
	Figure 10.10	AVL-dictionary insertion
	Chapter 11
	Figure 11.7	A depth-first search program that avoids cycling
	Figure 11.8	A depth-limited, depth-first search program
	Figure 11.10	An implementation of breadth-first search
	Figure 11.11	A more efficient program than that of Figure 11.10 for the breadth-first search
	Chapter 12
	Figure 12.3	A best-first search program
	Figure 12.6	Problem-specific procedures for the eight puzzle, to be used in best-first search of Figure 12.3
	Figure 12.9	Problem-specific relations for the task-scheduling problem
	Figure 12.10	An implementation of the IDA* algorithm
	Figure 12.13	A best-first search program that only requires space linear in the depth of search (RBFS algorithm)
	Chapter 13
	Figure 13.8	Depth-first search for AND/OR graphs
	Figure 13.12	Best-first AND/OR search program
	Chapter 14
	Figure 14.3	Scheduling with precedence constraints and no resource constraints
	Figure 14.4	A CLP(R) scheduling program for problems with precedence and resource constraints
	Figure 14.6	Constraints for some electrical components and connections
	Figure 14.7	Two electrical circuits
	Figure 14.8	A cryptarithmetic puzzle in CLP(FD)
	Figure 14.9	A CLP(FD) program for eight queens
	Chapter 15
	Figure 15.6	A backward chaining interpreter for if-then rules
	Figure 15.7	A forward chaining rule interpreter
	Figure 15.8	Generating proof trees
	Figure 15.9	An interpreter for rules with certainties
	Figure 15.11	An interpreter for belief networks
	Figure 15.12	A specification of the belief network of Fig. 15.10 as expected by the program of Fig. 15.11
	Figure 15.14	Some frames
	Chapter 16
	Figure 16.1	A simple knowledge base for identifying animals
	Figure 16.3	A knowledge base for identifying faults in an electric network
	File shell.txt	Figures 16.6, 16.7, 16.8, 16.9 combined, with small modifications, into an expert system shell
	Chapter 17
	Figure 17.2	A definition of the planning space for the blocks world
	Figure 17.3	A definition of the planning space for manipulating camera
	Figure 17.5	A simple means-ends planner
	Figure 17.6	A means-ends planner with goal protection
	Figure 17.8	A planner based on goal regression
	Figure 17.9	A state-space definition for means-ends planning based on goal regression
	Chapter 18
	Figure 18.9	Attribute definitions and examples for learning to recognize objects from their silhouettes (from Figure 18.8)
	Figure 18.11	A program that induces if-then rules
	File learn_tree.txt	Induction of decision trees (program sketched on pages 466-468)
	File prune_tree.txt	Solution to Exercise 18.6
	Chapter 19
	Figure 19.1	A definition of the problem of learning predicate has_daughter
	Figure 19.3	A loop-avoiding interpreter for hypotheses
	Figure 19.4	MINIHYPER - a simple ILP program
	Figure 19.5	Problem definition for learning list membership
	Figure 19.7	The HYPER program. The procedure prove/3 is as in Figure 19.3
	Figure 19.8	Learning about odd-length and even-length simultaneously
	Figure 19.9	Learning about a path in a graph
	Figure 19.10	Learning insertion sort
	Figure 19.12	Learning the concept of arch
	Chapter 20
	Figure 20.3	Qualitative modelling program for simple circuits
	Figure 20.8	A simulation program for qualitative differential equations
	Figure 20.9	A qualitative model of bath tub
	Figure 20.11	A qualitative model of the circuit in Figure 20.10
	Figure 20.14	A qualitative model of the block-spring system
	File energy.txt	An oscillator model with energy constraint (alternative to one in Fig. 20.14)
	Chapter 21
	Figure 21.6	A DCG handling the syntax and meaning of a small subset of natural language
	Chapter 22
	Figure 22.2	A game tree translated to Prolog
	Figure 22.3	A straightforward implementation of the minimax principle
	Figure 22.5	An implementation of the alpha-beta algorithm
	File chess.txt	Figures 22.6, 22.7, 22.10 combined into single file
	Chapter 23
	Figure 23.1	The basic Prolog meta-interpreter
	Figure 23.2	A Prolog meta-interpreter for tracing programs in pure Prolog
	Figure 23.3	Two problem definitions for explanation-based generalization
	Figure 23.4	Explanation-based generalization
	Figure 23.5	A simple interpreter for object-oriented programs
	Figure 23.6	An object-oriented program about geometric figures
	Figure 23.8	An object-oriented program about a robot world
	Figure 23.12	A pattern-directed program to find the greatest common divisor of a set of numbers
	Figure 23.13	A small interpreter for pattern-directed programs
	Figure 23.15	A pattern-directed program for simple resolution theorem proving
	Figure 23.16	Translating a propositional calculus formula into a set of (asserted) clauses
	All chapters
	List of codes and figures
	Prolog code for all chapters   (zip file)