Course - Artificial Intelligence MT24


Timetable

  • Wednesday 3PM-4PM, Bill Roscoe Lecture Theatre (weeks 1-6)
  • Friday 3PM-4PM, Bill Roscoe Lecture Theatre (weeks 1-8)
  • Friday 2PM-3PM, Bill Roscoe Lecture Theatre (weeks 7-8)

Notes

Some more notes on the course textbook are available in [[AI - A Modern Approach]]N, but the following are particularly relevant to this course:

Problem Sheets

Practicals

To-do List

  • Does $IDA^\star$ need a proof of optimality for admissible heuristics or does it follow immediately from the proof of optimality for ordinary $A^\star$?
  • Disjoint subproblems in general?
  • Proofs for completeness/optimality/time complexity/space complixty of uniformed and informed search algorithms
  • Details about building partial order plans
  • Understand faster implementation of the sweep algorithm
  • Does the Tree CSP algorithm only work when the CSP is binary?
  • Better understanding of tree decomposition algorithm, tree decompositions in general
    • There are three requirements, but is there another more basic one
  • Example for alpha beta search
  • Averaging over clairvoyance (13-14 playing games)
  • Go over problem sheet solutions



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