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• The course presentation form

The official week-by-week Faculty timetable can be found on the RIS BSc 3rd year.

• Main book: David Poole and Alan Mackworth. Artificial Intelligence: Foundations of Computational Agents. Cambridge University Press, 2010.
• Auxiliary book: Stuart Jonathan Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 2010.

You can read below which chapters of the above books are used in the various parts of the course.

• Slides: Welcome Aboard
• Slides: Artificial Intelligence and Agents part 1, part 2, part 3, part 4
  • Material: chapter 1 of Poole and Mackworth
• Slides: Agent Architectures and Hierarchical Control part 1, part 2
  • Material: chapter 2 of Poole and Mackworth
• Slides: States and Searching part 1, part 2, part 3, part 4
  • Material chapter 3 of Poole and Mackworth
• Slides: Features and Constraints part 1, part 2,
  • Material chapter 4 of Poole and Mackworth
• Slides: Propositions and Inference part 1, part 2, part 3, part 4, part 5, part 6, part 7, part 8, part 9
  • Material chapter 5 of Poole and Mackworth
• Slides: Individuals and Relations part 1, part 2, part 3, part 4, part 5, part 6, part 7, part 8, part on NL
  • Material chapter 12 of Poole and Mackworth
• Slides: Ontologies and Knowledge-Based Systems part 1, part 2, Introduction to RDF, RDF Semantics, E/R semantics, E/R and logic
  • Material chapter 13 of Poole and Mackworth, Introduction to RDF, Semantics of Conceptual Modelling

• LAB 1: Robot Control (applet).
• LAB 2: Graph Searching (applet):
  • Explore the Delivery Robot (Acyclic) and the Delivery Robot (cyclic) sample problem graphs: with Depth First, Breadth First, Lowest Cost First search strategies using different Neighbour Ordering Strategies.
  • Create your own problem graph for a delivery robot starting from a map with edge costs.
  • Create a problem graph for a simple problem chosen by you.
  • Do the Practice Exercises 2.* and 3.*.
• LAB 3:
  • Exercise: 3.3(a) - implement the depth-first and breadth-first search strategies.
  • Exercise: 3.4(a) - implement the lowest-cost-first search strategy.
• LAB 4:
  • Practise with iterative deepening, branch-and-bound, and bidirectional search strategies
  • Towers of Hanoi:
    • Exercise
    • the state graph (alternative version).
  • Search in Prolog with SWI Prolog
    • Depth-first and Breadth-first
• LAB 5
  • Consistency Based CSP Solver (applet):
    • Exercises: 4.2, 4.3, 4.5 - CSP and arc consistency.
• LAB 6
  • AILog2, a representation and reasoning system for definite clauses, with declarative debugging tools.
    • To start AILog just load the file ailog2.pl into SWI Prolog
    • Knowledge bases (complete set):
• LAB 7
  • Exercises: 5.1,5.2,5.6,5.7 - Propositions and Inference.
  • elect_prop.ail electrical wiring example; Example 5.5 from Section 5.2
  • elect_ask.ail electrical wiring example with askables; Example 5.10 from Section 5.3.2
  • elect_bug.ail the buggy electrical wiring knowledge base from Example 5.14 in Section 5.3.4
  • elect_bug2.ail the buggy electrical wiring example from Exercise 5.6
  • elect_bug3.ail a buggy electrical wiring example, which fails to prove lit_l2, but should succeed
• LAB 8
  • elect_cbd.ail electrical wiring example for consistency-based diagnosis; Example 5.20 in Section 5.4.3
  • elect_naf.ail electrical wiring example with negation as failure; Example 5.26 in Section 5.5
  • beach.ail default reasoning about swimming at beaches; Example 5.27 in Section 5.5.1
  • bronchitis.ail diagnosis Example 5.30 in Section 5.6
  • elect_abd.ail electrical wiring example with abduction; Example 5.31 in Section 5.6
  • plumbing.ail plumbing domain from Exercise 5.2
• LAB 9
  • Exercises: 12.3,12.6,12.10,12.12,12.15,12.16 - Individuals and Relations.
• LAB 10
  • AILog exercises (use extensively How?, Why not?, Why? questions and Depth Bound):
  • elect_relational.ail electrical wiring example from Section 12.3.2
  • west.ail a knowledge base about rooms from Figure 12.2 in Section 12.3.3
  • before.ail the before relation of Example 12.26 in Section 12.5
  • trees.ail the tree code of Example 12.27 in Section 12.5
• LAB 11
  • cfg_simple.ail a simple context free grammar and associated dictionary from Figures 12.6 and 12.7 in Section 12.5 (also in Prolog)
  • trans.ail generates canned English; from Figure 12.8 in Section 12.6.4 (also in Prolog)
  • nl_numbera.ail a simple grammar that enforces number agreement and builds a parse tree; from Figure 12.9 in Section 12.6.5 (also in Prolog)
  • nl_interface.ail a simple natural language interface to a database; from Figures 12.10 and 12.11 in Section 12.6.6 (also in Prolog)
• Exercises: play with the ICOM conceptual modelling system.

The midterm will be on the 27th of November 2014 at 8:30-10:30. It will cover the first three chapters of the textbook.

• Solve a given problem as a search problem in the space of states induced by the possible transitions. Use both depth-first and breadth-first uninformed search strategies, and any heuristic search strategy of your choice. Choose an appropriate representation for states, and implement a transition function devising neighbour states. Pay attention to cycle detection whenever it is necessary, and discuss its impact. Discuss possible heuristic functions you may apply to the problem. Compare the different search strategies (with different heuristics) with respect to the efficiency in finding the solution(s) and the optimality of the solution(s) found, and discuss the differences.

• Results Midterm A 2012/2013

• Solve a problem in the area of CSP or of Propositional Rules using the software already provided at the lab: the Consistency Based CSP Solver and AILog.
• Upload the midterm as a single file: :teaching:is:midterm-b:
• Results Midterm B 2012/2013

• Results Exam 1 2012/2013
• Results 2014-15 February 2015 session: